critical analysis of case study example

Case Study Analysis: Examples + How-to Guide & Writing Tips

A case study analysis is a typical assignment in business management courses. The task aims to show high school and college students how to analyze a current situation, determine what problems exist, and develop the best possible strategy to achieve the desired outcome.

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Many students feel anxious about writing case analyses because being told to analyze a case study and provide a solution can seem like a big task. That is especially so when working with real-life scenarios. However, you can rest assured writing a case analysis paper is easier than you think. Just keep reading this article and you will find case study examples for students and the advice provided by Custom-writing experts!

• 👣 Main Steps
• 🕵 Preparing the Case

🔬 Analyzing the Case

• 📑 Format & Structure
• 🙅 Things to Avoid
• 🏁 Conclusion

🔗 References

👣 writing a case study analysis: main steps.

Business management is built on case analysis. Every single economic result shows that the methods and instruments employed were either well-timed and expedient, in the event of success, or not, in case of failure. These two options indicate whether the strategy is efficient (and should be followed) or requires corrections (or complete change). Such an approach to the case study will make your writing piece more proficient and valuable for the reader. The following steps will direct your plan for writing a case study analysis.

Step 1: Preliminary work

• Make notes and highlight the numbers and ideas that could be quoted.
• Single out as many problems as you can, and briefly mark their underlying issues. Then make a note of those responsible. In the report, you will use two to five of the problems, so you will have a selection to choose from.
• Outline a possible solution to each of the problems you found. Course readings and outside research shall be used here. Highlight your best and worst solution for further reference.

Step 2: Drafting the Case

• Provide a general description of the situation and its history.
• Name all the problems you are going to discuss.
• Specify the theory used for the analysis.
• Present the assumptions that emerged during the analysis, if any.
• Describe the detected problems in more detail.
• Indicate their link to, and effect on, the general situation.
• Explain why the problems emerged and persist.
• List realistic and feasible solutions to the problems you outlined, in the order of importance.
• Specify your predicted results of such changes.
• Support your choice with reliable evidence (i.e., textbook readings, the experience of famous companies, and other external research).
• Define the strategies required to fulfill your proposed solution.
• Indicate the responsible people and the realistic terms for its implementation.
• Recommend the issues for further analysis and supervision.

Step 3: Finalizing the Case

Like any other piece of writing, a case analysis requires post-editing. Carefully read it through, looking for inconsistencies and gaps in meaning. Your purpose is to make it look complete, precise, and convincing.

🕵 Preparing a Case for Analysis

Your professor might give you various case study examples from which to choose, or they may just assign you a particular case study. To conduct a thorough data analysis, you must first read the case study. This might appear to be obvious. However, you’d be surprised at how many students don’t take adequate time to complete this part.

Read the case study very thoroughly, preferably several times. Highlight, underline, flag key information, and make notes to refer to later when you are writing your analysis report.

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If you don’t have a complete knowledge of the case study your professor has assigned, you won’t conduct a proper analysis of it. Even if you make use of a business case study template or refer to a sample analysis, it won’t help if you aren’t intimately familiar with your case study.

You will also have to conduct research. When it comes to research, you will need to do the following:

• Gather hard, quantitative data (e.g. 67% of the staff participated in the meeting).
• Design research tools , such as questionnaires and surveys (this will aid in gathering data).
• Determine and suggest the best specific, workable solutions.

It would be best if you also learned how to analyze a case study. Once you have read through the case study, you need to determine the focus of your analysis. You can do this by doing the following:

Compare your chosen solutions to the solutions offered by the experts who analyzed the case study you were given or to online assignments for students who were dealing with a similar task. The experts’ solutions will probably be more advanced than yours simply because these people are more experienced. However, don’t let this discourage you; the whole point of doing this analysis is to learn. Use the opportunity to learn from others’ valuable experience, and your results will be better next time.

If you are still in doubt, the University of South Carolina offers a great guide on forming a case study analysis.

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📑 Case Analysis Format & Structure

When you are learning how to write a case study analysis, it is important to get the format of your analysis right. Understanding the case study format is vital for both the professor and the student. The person planning and handing out such an assignment should ensure that the student doesn’t have to use any external sources .

In turn, students have to remember that a well-written case analysis provides all the data, making it unnecessary for the reader to go elsewhere for information.

Regardless of whether you use a case study template, you will need to follow a clear and concise format when writing your analysis report. There are some possible case study frameworks available. Still, a case study should contain eight sections laid out in the following format:

• Describe the purpose of the current case study;
• Provide a summary of the company;
• Briefly introduce the problems and issues found in the case study
• Discuss the theory you will be using in the analysis;
• Present the key points of the study and present any assumptions made during the analysis.
• Present each problem you have singled out;
• Justify your inclusion of each problem by providing supporting evidence from the case study and by discussing relevant theory and what you have learned from your course content;
• Divide the section (and following sections) into subsections, one for each of your selected problems.
• Present a summary of each problem you have identified;
• Present plausible solutions for each of the problems, keeping in mind that each problem will likely have more than one possible solution;
• Provide the pros and cons of each solution in a way that is practical.
• Conclusion . This is a summary of your findings and discussion.
• Decide which solution best fits each of the issues you identified;
• Explain why you chose this solution and how it will effectively solve the problem;
• Be persuasive when you write this section so that you can drive your point home;
• Be sure to bring together theory and what you have learned throughout your course to support your recommendations.
• Provide an explanation of what must be done, who should take action, and when the solution should be carried out;
• Where relevant, you should provide an estimate of the cost in implementing the solution, including both the financial investment and the cost in terms of time.
• References. While you generally do not need to refer to many external sources when writing a case study analysis, you might use a few. When you do, you will need to properly reference these sources, which is most often done in one of the main citation styles, including APA, MLA, or Harvard. There is plenty of help when citing references, and you can follow these APA guidelines , these MLA guidelines , or these Harvard guidelines .
• Appendices. This is the section you include after your case study analysis if you used any original data in the report. These data, presented as charts, graphs, and tables, are included here because to present them in the main body of the analysis would be disruptive to the reader. The University of Southern California provides a great description of appendices and when to make use of them.

When you’ve finished your first draft, be sure to proofread it. Look not only for potential grammar and spelling errors but also for discrepancies or holes in your argument.

You should also know what you need to avoid when writing your analysis.

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🙅 Things to Avoid in Case Analysis

Whenever you deal with a case study, remember that there are some pitfalls to avoid! Beware of the following mistakes:

• Excessive use of colloquial language . Even though it is a study of an actual case, it should sound formal.
• Lack of statistical data . Give all the important data, both in percentages and in numbers.
• Excessive details. State only the most significant facts, rather than drowning the reader in every fact you find.
• Inconsistency in the methods you have used . In a case study, theory plays a relatively small part, so you must develop a specific case study research methodology.
• Trivial means of research . It is critical that you design your own case study research method in whatever form best suits your analysis, such as questionnaires and surveys.

It is useful to see a few examples of case analysis papers. After all, a sample case study report can provide you with some context so you can see how to approach each aspect of your paper.

👀 Case Study Examples for Students

It might be easier to understand how a case study analysis works if you have an example to look at. Fortunately, examples of case studies are easy to come by. Take a look at this video for a sample case study analysis for the Coca-Cola Company.

If you want another example, then take a look at the one below!

Business Case Analysis: Example

CRM’s primary focus is customers and customer perception of the brand or the company. The focus may shift depending on customers’ needs. The main points that Center Parcs should consider are an increase in customer satisfaction and its market share. Both of these points will enhance customer perception of the product as a product of value. Increased customer satisfaction will indicate that the company provides quality services, and increased market share can reduce the number of switching (or leaving) customers, thus fostering customer loyalty.

Case Study Topics

• Equifax case study: the importance of cybersecurity measures . 
• Study a case illustrating ethical issues of medical research.  
• Examine the case describing the complications connected with nursing and residential care.  
• Analyze the competitive strategy of Delta Airlines . 
• Present a case study of an ethical dilemma showing the conflict between the spirit and the letter of the law.  
• Explore the aspects of Starbucks’ marketing strategyin a case study.  
• Research a case of community-based clinic organization and development.  
• Customer service of United Airlines: a case study . 
• Analyze a specific schizophrenia case and provide your recommendations.  
• Provide a case study of a patient with hyperglycemia.  
• Examine the growth strategy of United Healthcare. 
• Present a case study demonstrating ethical issues in business .  
• Study a case of the 5% shareholding rule application and its impact on the company.  
• Case study of post-traumatic stress disorder . 
• Analyze a case examining the issues of cross-cultural management .  
• Write a case study exploring the ethical issues the finance manager of a long-term care facility can face and the possible reaction to them.  
• Write a case study analyzing the aspects of a new president of a firm election. 
• Discuss the specifics of supply chain management in the case of Tehindo company. 
• Study a case of a life crisis in a family and the ways to cope with it.  
• Case study of Tea Leaves and More: supply chain issues .   
• Explore the case of ketogenic diet implementation among sportspeople.  
• Analyze the case of Webster Jewelry shop and suggest some changes.  
• Examine the unique aspects of Tea and More brand management .  
• Adidas case study: an ethical dilemma .  
• Research the challenges of Brazos Valley Food Bank and suggest possible solutions.  
• Describe the case of dark web monitoring for business.  
• Study a case of permissive parenting style .  
• Case study of Starbucks employees . 
• Analyze a case of workplace discrimination and suggest a strategy to avoid it.  
• Examine a case of the consumer decision-making process and define the factors that influence it.  
• Present a case study of Netflix illustrating the crucial role of management innovation for company development.  
• Discuss a case describing a workplace ethical issue and propose ways to resolve it.  
• Case study of the 2008 financial crisis: Graham’s value investing principles in the modern economic climate. 
• Write a case study analyzing the harmful consequences of communication issues in a virtual team .  
• Analyze a case that highlights the importance of a proper functional currency choice. 
• Examine the case of Hitachi Power Systems management.  
• Present a case study of medication research in a healthcare facility.  
• Study the case of Fiji Water and the challenges the brand faces.  
• Research a social problem case and suggest a solution.  
• Analyze a case that reveals the connection between alcohol use and borderline personality disorder .  
• Transglobal Airline case study: break-even analysis.   
• Examine the case of Chiquita Brands International from the moral and business ethics points of view.  
• Present a case study of applying for Social Security benefits. 
• Study the case of a mass hacker attack on Microsoft clients and suggest possible ways to prevent future attacks.  
• Case study of leadership effectiveness . 
• Analyze a case presenting a clinical moral dilemma and propose ways to resolve it. 
• Describe the case of Cowbell Brewing Company and discuss the strategy that made them successful.  
• Write a case study of WeWork company and analyze the strengths and weaknesses of its strategy.  
• Case study of medical ethical decision-making. 
• Study the case of The Georges hotel and suggest ways to overcome its managerial issues.  

🏁 Concluding Remarks

Writing a case study analysis can seem incredibly overwhelming, especially if you have never done it before. Just remember, you can do it provided you follow a plan, keep to the format described here, and study at least one case analysis example.

If you still need help analyzing a case study, your professor is always available to answer your questions and point you in the right direction. You can also get help with any aspect of the project from a custom writing company. Just tackle the research and hand over the writing, write a rough draft and have it checked by a professional, or completely hand the project off to an expert writer.

Regardless of the path you choose, you will turn in something of which you can be proud!

✏️ Case Study Analysis FAQ

Students (especially those who study business) often need to write a case study analysis. It is a kind of report that describes a business case. It includes multiple aspects, for example, the problems that exist, possible solutions, forecasts, etc.

There should be 3 main points covered in a case study analysis:

• The challenge(s) description,
• Possible solutions,
• Outcomes (real and/or foreseen).

Firstly, study some examples available online and in the library. Case study analysis should be a well-structured paper with all the integral components in place. Thus, you might want to use a template and/or an outline to start correctly.

A case study analysis is a popular task for business students. They typically hand it in the format of a paper with several integral components:

• Description of the problem
• Possible ways out
• Results and/or forecasts

Students sometimes tell about the outcome of their research within an oral presentation.

• Case Study: Academia
• Windows of vulnerability: a case study analysis (IEEE)
• A (Very) Brief Refresher on the Case Study Method: SAGE
• The case study approach: Medical Research Methodology
• Strengths and Limitations of Case Studies: Stanford University
• A Sample APA Paper: Radford University
• How to Write a Case Study APA Style: Seattle PI
• The Case Analysis: GVSU
• How to Outline: Purdue OWL
• Incorporating Interview Data: UW-Madison Writing Center
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This article was very helpful, even though I’ll have a clearer mind only after I do the case study myself but I felt very much motivated after reading this, as now I can at least have a plan of what to do compared to the clueless me I was before I read it. I hope if I have any questions or doubts about doing a case study I can clear it out here.

The Ultimate Guide on Writing an A+ Case Study Analysis + 15 Examples

Struggle with writing a case study analysis? You are in the right place! Below, we will show you nuts and bolts of this type of paper, how to write it, and share 15 distinct essay examples. Plus, you will find the case study checklist to keep your writing on track.

What is a Case Study Analysis?

Case study analysis topics.

• Important Aspects

You might ask, what is a case study analysis ? With this type of work, you take an actual situation from a specific discipline, such as business or education. The goal is to find a solution, analyze the outcomes of the situation, or evaluate it.

Case study analysis does not target one specific theory or piece of knowledge. It requires a universal application of several theories and methods for research and review. Hence, it can be helpful for many disciplines at once. If you need to look at some examples, head over to our essay database .

There are several steps you need to take for a successful analysis depending on the type of your case study. Here are the most critical universal points:

• Analyze the problem from different perspectives. Use the theories and methods you have learned about in the classroom.
• Devise a series of solutions or outcomes. You need to analyze their advantages and weaknesses.
• Provide the best solution according to your analysis. You must present solid arguments for why you have suggested it.
• Demonstrate well-grounded research in your case study analysis You should not make claims without proof.
• Provide credible references for any theory that you mention in your analysis. You do not want your work to be discarded because of plagiarism.

If you want to start the business in the future, case study analysis is essential for your education. It can give you a taste of what your career is might include.

Are you panicking because you have never written anything like this before? Don’t worry! After going through the guidelines in this article, you will get a better sense of what is required from you. It will not seem as scary anymore. 😊

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15 Case Study Analysis Examples

We have prepared 15 examples of case study analysis, so you can get an idea of how they should look. The disciplines are broad and there is something here for everyone. Check out the table below!

Let’s concentrate on the format for case study analysis!

Case Study Analysis: Format

In this section, we will get you acquainted with different types of case studies. We will focus on the difference between multiple and single case study analysis. Additionally, we will show you how to organize all of your ideas into an outline. Hence, your work will be understandable and complete.

• Types of Case Studies

There are several distinct types of case studies , each with its nuances. The choice will depend on the needs of your investigation. We will focus on Illustrative, Exploratory, Cumulative, and Critical Instance studies. Let’s explore each of them one by one.

• Illustrative Case Studies Illustrative case studies are the most common type. They are very descriptive, and the main goal is to help you understand the situation. You are typically given one or two instances of an event. Illustrative case studies answer two questions: What is happening? Why is it happening? The case study is explained in great detail, including location, key players, roles, influence, and involvement. The focus of illustrative case studies is to maintain the reader’s interest. Hence, the language should be understandable, but it should not be oversimplified. It is not preferred to quote more than two instances as the case study might become too complicated.
• Exploratory Case Studies Exploratory case studies are mainly used in Social Sciences. They tend to focus on real-life contexts for situations. They are implemented before a large-scale investigation to help develop the case for more advanced research processes. Exploratory case studies aim to research a specific topic in detail to help you reach a complete understanding of it. You need to identify questions that can later be answered as part of a more extensive examination. Your initial research might reveal very persuasive details. However, it is crucial to remember that concluding before the large-scale investigation is counterproductive.
• Cumulative Case Studies The idea of a cumulative case study is to gather information and details from many data sources to claim a general phenomenon. Cumulative case studies eliminate the need for additional and expensive new studies, which are simply repetitions of the old ones. If you properly analyze all of the case study data that exists, you will realize that everything you are looking for is already there. However, it is essential to look at the existing research from a new perspective to ensure it fits the current challenges and needs.
• Critical Instance Case Studies Critical instance case studies are similar to cumulative but work oppositely. Instead of defining a general phenomenon based on little research, it tries to understand a specific case based on generalized findings. Critical instance case studies help answer cause and effect questions. The adequate specification of your evaluation question is the most crucial part of your analysis.
• Single vs. Multiple Case Study

Your case study can either include a single case or multiple cases . In this section, we will discuss the benefits of both:

• Single Case Study Single case studies are less expensive and do not take as much time. When examining one case, it is easier to put all of your energy into it and get a deeper understanding of the subject. Since the study is more careful, you can look at one thing from many different perspectives. Usually, in a single case study, the case is more critical and unique , and it is possible to focus on a more longitudinal research.
• Multiple Case Study When studying several cases, you can understand the critical similarities and differences among them. If you base your research on many cases, it will be more robust and reliable. Such analysis allows you to form broader research questions. Hence, you can end up with a more convincing theory.

Now, let’s talk about the backbone of every study: the outline!

Case Study Outline

Before writing any paper, you should first prepare an outline. It not only makes your job easier but also enhances the organization of your paper. You should put all of your ideas down and try to understand which order and format will best suit your analysis.

We have tried to simplify the process by preparing a sample outline for your case study analysis. It will help you understand what your paper should include.

• Introduction Firstly, you should introduce your reader to the case, assuming they have no prior knowledge. Describe all the challenges and mention the most important details.
• Answers to the Questions There will probably be some questions about your case. It would be best if you answered all of them in an organized manner. Make sure not to make it too obvious. Answer them in such a way that it seems like a part of your analysis.
• Challenges Though you talk about the challenges in your introduction a little bit, it is essential to go into more detail within the main paragraphs to make sure your readers understand them. It will improve the comprehension of solutions later.
• Solutions Introduce each solution you have devised. Evaluate those based on different theories and mechanisms. All of your propositions need to be solid and well-designed. Your case study evaluation should be informative and engaging.
• Final Statement In this part of your paper, you should state which solution best fits the case according to your broader analysis. You should compare it with the others and explain why you have chosen it.
• Conclusion The conclusion is the last thing you need to write. There is nothing specific that should be included. Make sure that your paper comes to a logical end.
• References Of course, you need to reference all of the theories and practices mentioned in your paper for your analysis to be solid and well-grounded. The style of your references will depend on the format assigned by your instructor.

This is how a typical case study analysis should look like. We mentioned this format for you to imagine the standard thought process that goes into making outlines. First, organize your research and divide it into parts to achieve an exciting and compelling paper. The type of case study analysis with which you are dealing also matters.

Now, here’s how you start writing!

How to Write Case Study Analysis: Important Aspects

In this section, you will find everything you need to kickstart writing your paper. Firstly, we will go through the things you need to have ready before you start. Then, we will show you how to do adequate research. Finally, we will give you a case study checklist to make it easier to complete the tasks throughout your analysis.

Before You Start

It is vital to choose an appropriate case study topic first. It should be exciting and relevant to your area of study. Once you select your topic, you need to choose an applicable case study . There are several criteria that you need to keep in mind in your search of a case study:

• The case study should complement your topic of research For example, if the topic you have chosen is related to marketing, it would be weird if your case study was about banking. However, a case study about how a famous company handles its marketing would be very acceptable.
• The case study should apply to the phenomena that you have chosen to research Make sure that the way the company handles its marketing can be generalized to benefit other companies. It needs to be universally reusable.
• The case study cannot be outdated You need to know that you can apply the outcome of your research to the modern world. Everything needs to be analyzed from the perspective of today.
• Decide whether you need a single or multiple case study You can go through the comparison above once again. Try to understand which one suits your topic best.

Do you already have the topic? Let’s get your researching skills up to date!

Case Study Research

When doing case study research, simply googling something rains down tons of sources full of information. However, most of those sources cannot be trusted, especially when writing an academic paper. The references are the most crucial part of such papers. If they are poor, then your essay has no reliable basis. Hence, you need to look for official sources, such as university websites or scholarly articles. Remember that Wikipedia is not a valid source !

Throughout the process, have your research question in mind. It is easy to get carried away and read every exciting article on the topic. Nonetheless, it would be best to have a specific goal to ensure your research is practical and not wasting your time.

Finally, keep your research up to date! Remember that you are looking for information that applies to the current world and its challenges. You need to look for modern solutions to the given problem.

We are almost there! Let’s make sure you can tick off every item in this checklist !

Checklist for Case Study Analysis

Go through this checklist. It will help you keep your case study research and writing on track.

• Choose the topic.
• Decide whether you are going to do single or multiple case study.
• Identify the type of your case study.
• They are relevant to the topic.
• Their outcome can be generalized to fit other cases within the same area of research.
• They are not outdated.
• Define a clear case study research question.
• Make sure that the sources of your research are credible and up to date.
• Identify the theories and methodologies you are going to use to analyze the case.
• Use more than one point of view to examine the case, and look at it from different perspectives.
• Have a clear outline of what you are going to include in your paper.
• Write and proofread your paper.

Have you completed every item on this list? Congratulations! You are done with your case study analysis!

❓ What is the difference between case study and case analysis?

Case study and case analysis both provide you with a topic and require extensive research. However, a case study must be taken from real life. For example, a student might analyze Coca-Cola’s financial results and come up with brilliant results that can significantly impact the company. If you send this kind of case study analysis to the company, you might even get a reward. Case analysis focuses more on problems and solutions, whereas case studies can include general research and evaluation.

❓ What are the stages of a case study?

There are four main stages of a case study:

• analyzing the case,
• identifying its challenges,
• devising a set of possible solutions or outcomes,
• evaluating those outcomes.

To ensure the success of your analysis, you should go over all of these stages with equal diligence.

❓ What is the purpose of a case study?

The purpose of a case study analysis is to describe a case in detail and identify the main issues with it. Afterwards, these issues need to be analyzed based on appropriate theories from the discipline that you have learned about in class. Finally, you need to recommend a list of actions that should be performed for that case.

❓ What are the qualities of a good case study?

Here are some qualities of a good case study:

• It is written in a formal, academic language with good grammar and coherent structure.
• All of the claims made in the case study have a reasonable basis and can be proven.
• The case study does not overload the readers with unnecessary information. It is clear and to the point.
• The information is passed to the reader in an organized manner. It has flow, and it is easy to keep up with the extensive academic research.
• What is a Case Study Analysis
• Illustrative Case Studies
• Exploratory Case Study Example
• Definition of Cumulative Case Studies
• Definition of Critical Instance Case Studies
• A Comparative Study of Single and Multiple Case Studies
• How to Choose an Applicable Study
• Case Study Checklist
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15.7 Evaluation: Presentation and Analysis of Case Study

Learning outcomes.

By the end of this section, you will be able to:

• Revise writing to follow the genre conventions of case studies.
• Evaluate the effectiveness and quality of a case study report.

Case studies follow a structure of background and context , methods , findings , and analysis . Body paragraphs should have main points and concrete details. In addition, case studies are written in formal language with precise wording and with a specific purpose and audience (generally other professionals in the field) in mind. Case studies also adhere to the conventions of the discipline’s formatting guide ( APA Documentation and Format in this study). Compare your case study with the following rubric as a final check.

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Access for free at https://openstax.org/books/writing-guide/pages/1-unit-introduction

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How to Write a Case Study Analysis

Step-By-Step Instructions

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When writing a business case study analysis , you must first have a good understanding of the case study . Before you begin the steps below, read the business case carefully, taking notes all the while. It may be necessary to read the case several times to get all of the details and fully grasp the issues facing the group, company, or industry.

As you are reading, do your best to identify key issues, key players, and the most pertinent facts. After you are comfortable with the information, use the following step-by-step instructions (geared toward a single-company analysis) to write your report. To write about an industry, just adapt the steps listed here to discuss the segment as a whole.

Step 1: Investigate the Company’s History and Growth

A company’s past can greatly affect the present and future state of the organization. To begin, investigate the company’s founding, critical incidents, structure, and growth. Create a timeline of events, issues, and achievements. This timeline will come in handy for the next step. 

Step 2: Identify Strengths and Weaknesses

Using the information you gathered in step one, continue by examining and making a list of the value creation functions of the company. For example, the company may be weak in product development but strong in marketing. Make a list of problems that have occurred and note the effects they have had on the company. You should also list areas where the company has excelled. Note the effects of these incidents as well.

You're essentially conducting a partial SWOT analysis to get a better understanding of the company's strengths and weaknesses. A SWOT analysis involves documenting things like internal strengths (S) and weaknesses (W) and external opportunities (O) and threats (T). 

Step 3: Examine the External Environment

The third step involves identifying opportunities and threats within the company’s external environment. This is where the second part of the SWOT analysis (the O and the T) comes into play. Special items to note include competition within the industry, bargaining powers, and the threat of substitute products. Some examples of opportunities include expansion into new markets or new technology. Some examples of threats include increasing competition and higher interest rates.

Step 4: Analyze Your Findings

Using the information in steps 2 and 3, create an evaluation for this portion of your case study analysis. Compare the strengths and weaknesses within the company to the external threats and opportunities. Determine if the company is in a strong competitive position, and decide if it can continue at its current pace successfully.

Step 5: Identify Corporate-Level Strategy

To identify a company’s corporate-level strategy, identify and evaluate the company’s mission , goals, and actions toward those goals. Analyze the company’s line of business and its subsidiaries and acquisitions. You also want to debate the pros and cons of the company strategy to determine whether or not a change might benefit the company in the short or long term.​

Step 6: Identify Business-Level Strategy

Thus far, your case study analysis has identified the company’s corporate-level strategy. To perform a complete analysis, you will need to identify the company’s business-level strategy. (Note: If it is a single business, without multiple companies under one umbrella, and not an industry-wide review, the corporate strategy and the business-level strategy are the same.) For this part, you should identify and analyze each company’s competitive strategy, marketing strategy, costs, and general focus.

Step 7: Analyze Implementations

This portion requires that you identify and analyze the structure and control systems that the company is using to implement its business strategies. Evaluate organizational change, levels of hierarchy, employee rewards, conflicts, and other issues that are important to the company you are analyzing.

Step 8: Make Recommendations

The final part of your case study analysis should include your recommendations for the company. Every recommendation you make should be based on and supported by the context of your analysis. Never share hunches or make a baseless recommendation.

You also want to make sure that your suggested solutions are actually realistic. If the solutions cannot be implemented due to some sort of restraint, they are not realistic enough to make the final cut.

Finally, consider some of the alternative solutions that you considered and rejected. Write down the reasons why these solutions were rejected. 

Step 9: Review

Look over your analysis when you have finished writing. Critique your work to make sure every step has been covered. Look for grammatical errors , poor sentence structure, or other things that can be improved. It should be clear, accurate, and professional.

Business Case Study Analysis Tips

Keep these strategic tips in mind:

• Know the case study ​backward and forward before you begin your case study analysis.
• Give yourself enough time to write the case study analysis. You don't want to rush through it.
• Be honest in your evaluations. Don't let personal issues and opinions cloud your judgment.
• Be analytical, not descriptive.
• Proofread your work, and even let a test reader give it a once-over for dropped words or typos that you no longer can see.
• How to Write and Format a Business Case Study
• MBA Case Studies From Top Business Schools
• Business Case Competitions: Purpose, Types and Rules
• Components of a Business Plan
• How to Write a Case Brief
• How to Get Good Grades in Business School
• What Is Proposal Writing?
• What to Expect From MBA Classes
• How to Write a 10-Page Research Paper
• How To Write a Top-Scoring ACT Essay for the Enhanced Writing Test
• How to Write a Letter of Recommendation
• How to Write a Descriptive Paragraph
• How to Write a Functional Behavior Analysis
• What You Can Do With an MBA
• How to Write a Business Report for English Learners
• Critical Thinking Definition, Skills, and Examples

Organizing Your Social Sciences Research Assignments

• Annotated Bibliography
• Analyzing a Scholarly Journal Article
• Group Presentations
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• Types of Structured Group Activities
• Group Project Survival Skills
• Leading a Class Discussion
• Multiple Book Review Essay
• Reviewing Collected Works
• Writing a Case Analysis Paper
• Writing a Case Study
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Reflective Paper
• Writing a Research Proposal
• Generative AI and Writing
• Acknowledgments

A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate  key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies. Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in the Organizing Your Social Sciences Research Paper writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

• The case represents an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
• The case provides important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
• The case challenges and offers a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in current practice. A case study analysis may offer an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
• The case provides an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings so as to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
• The case offers a new direction in future research? A case study can be used as a tool for an exploratory investigation that highlights the need for further research about the problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of east central Africa. A case study of how women contribute to saving water in a rural village of Uganda can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community. This example of a case study could also point to the need for scholars to build new theoretical frameworks around the topic [e.g., applying feminist theories of work and family to the issue of water conservation].

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work.

In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

• What is being studied? Describe the research problem and describe the subject of analysis [the case] you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
• Why is this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
• What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
• How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II.  Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and  enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

• Place relevant works in the context of their contribution to understanding the case study being investigated . This would involve summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
• Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to investigate the research problem and the underlying research questions.
• Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your use of a case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
• Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
• Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
• Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
• Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in relation to explaining the relevance of the case in addressing the research problem.

III.  Method

In this section, you explain why you selected a particular case [i.e., subject of analysis] and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that constitutes your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; and, c) what were the consequences of the event in relation to the research problem.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experiences they have had that provide an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of their experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using them as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem [e.g., why is one politician in a particular local election used to show an increase in voter turnout from any other candidate running in the election]. Note that these issues apply to a specific group of people used as a case study unit of analysis [e.g., a classroom of students].

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, historical, cultural, economic, political], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, explain why you are studying Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research suggests Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut off? How might knowing the suppliers of these trucks reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE:   The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should clearly support investigation of the research problem and linked to key findings from your literature review. Be sure to cite any studies that helped you determine that the case you chose was appropriate for examining the problem.

IV.  Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your analysis of the case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is common to combine a description of the results with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings Remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations revealed by the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research if that is how the findings can be interpreted from your case.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V.  Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and any need for further research.

The function of your paper's conclusion is to: 1) reiterate the main argument supported by the findings from your case study; 2) state clearly the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

• If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
• If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in or the preferences of your professor, the concluding paragraph may contain your final reflections on the evidence presented as it applies to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were engaged with social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood more in terms of managing access rather than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis that leave the reader questioning the results.

Case Studies. Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009;  Kratochwill,  Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education .  Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 :  General, theoretical [context-independent] knowledge is more valuable than concrete, practical [context-dependent] knowledge. Misunderstanding 2 :  One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 :  The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 :  The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 :  It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

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Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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33 Critical Analysis Examples

Critical analysis refers to the ability to examine something in detail in preparation to make an evaluation or judgment.

It will involve exploring underlying assumptions, theories, arguments, evidence, logic, biases, contextual factors, and so forth, that could help shed more light on the topic.

In essay writing, a critical analysis essay will involve using a range of analytical skills to explore a topic, such as:

• Evaluating sources
• Exploring strengths and weaknesses
• Exploring pros and cons
• Questioning and challenging ideas
• Comparing and contrasting ideas

If you’re writing an essay, you could also watch my guide on how to write a critical analysis essay below, and don’t forget to grab your worksheets and critical analysis essay plan to save yourself a ton of time:

Grab your Critical Analysis Worksheets and Essay Plan Here

Critical Analysis Examples

1. exploring strengths and weaknesses.

Perhaps the first and most straightforward method of critical analysis is to create a simple strengths-vs-weaknesses comparison.

Most things have both strengths and weaknesses – you could even do this for yourself! What are your strengths? Maybe you’re kind or good at sports or good with children. What are your weaknesses? Maybe you struggle with essay writing or concentration.

If you can analyze your own strengths and weaknesses, then you understand the concept. What might be the strengths and weaknesses of the idea you’re hoping to critically analyze?

Strengths and weaknesses could include:

• Does it seem highly ethical (strength) or could it be more ethical (weakness)?
• Is it clearly explained (strength) or complex and lacking logical structure (weakness)?
• Does it seem balanced (strength) or biased (weakness)?

You may consider using a SWOT analysis for this step. I’ve provided a SWOT analysis guide here .

2. Evaluating Sources

Evaluation of sources refers to looking at whether a source is reliable or unreliable.

This is a fundamental media literacy skill .

Steps involved in evaluating sources include asking questions like:

• Who is the author and are they trustworthy?
• Is this written by an expert?
• Is this sufficiently reviewed by an expert?
• Is this published in a trustworthy publication?
• Are the arguments sound or common sense?

For more on this topic, I’d recommend my detailed guide on digital literacy .

3. Identifying Similarities

Identifying similarities encompasses the act of drawing parallels between elements, concepts, or issues.

In critical analysis, it’s common to compare a given article, idea, or theory to another one. In this way, you can identify areas in which they are alike.

Determining similarities can be a challenge, but it’s an intellectual exercise that fosters a greater understanding of the aspects you’re studying. This step often calls for a careful reading and note-taking to highlight matching information, points of view, arguments or even suggested solutions.

Similarities might be found in:

• The key themes or topics discussed
• The theories or principles used
• The demographic the work is written for or about
• The solutions or recommendations proposed

Remember, the intention of identifying similarities is not to prove one right or wrong. Rather, it sets the foundation for understanding the larger context of your analysis, anchoring your arguments in a broader spectrum of ideas.

Your critical analysis strengthens when you can see the patterns and connections across different works or topics. It fosters a more comprehensive, insightful perspective. And importantly, it is a stepping stone in your analysis journey towards evaluating differences, which is equally imperative and insightful in any analysis.

4. Identifying Differences

Identifying differences involves pinpointing the unique aspects, viewpoints or solutions introduced by the text you’re analyzing. How does it stand out as different from other texts?

To do this, you’ll need to compare this text to another text.

Differences can be revealed in:

• The potential applications of each idea
• The time, context, or place in which the elements were conceived or implemented
• The available evidence each element uses to support its ideas
• The perspectives of authors
• The conclusions reached

Identifying differences helps to reveal the multiplicity of perspectives and approaches on a given topic. Doing so provides a more in-depth, nuanced understanding of the field or issue you’re exploring.

This deeper understanding can greatly enhance your overall critique of the text you’re looking at. As such, learning to identify both similarities and differences is an essential skill for effective critical analysis.

My favorite tool for identifying similarities and differences is a Venn Diagram:

To use a venn diagram, title each circle for two different texts. Then, place similarities in the overlapping area of the circles, while unique characteristics (differences) of each text in the non-overlapping parts.

6. Identifying Oversights

Identifying oversights entails pointing out what the author missed, overlooked, or neglected in their work.

Almost every written work, no matter the expertise or meticulousness of the author, contains oversights. These omissions can be absent-minded mistakes or gaps in the argument, stemming from a lack of knowledge, foresight, or attentiveness.

Such gaps can be found in:

• Missed opportunities to counter or address opposing views
• Failure to consider certain relevant aspects or perspectives
• Incomplete or insufficient data that leaves the argument weak
• Failing to address potential criticism or counter-arguments

By shining a light on these weaknesses, you increase the depth and breadth of your critical analysis. It helps you to estimate the full worth of the text, understand its limitations, and contextualize it within the broader landscape of related work. Ultimately, noticing these oversights helps to make your analysis more balanced and considerate of the full complexity of the topic at hand.

You may notice here that identifying oversights requires you to already have a broad understanding and knowledge of the topic in the first place – so, study up!

7. Fact Checking

Fact-checking refers to the process of meticulously verifying the truth and accuracy of the data, statements, or claims put forward in a text.

Fact-checking serves as the bulwark against misinformation, bias, and unsubstantiated claims. It demands thorough research, resourcefulness, and a keen eye for detail.

Fact-checking goes beyond surface-level assertions:

• Examining the validity of the data given
• Cross-referencing information with other reliable sources
• Scrutinizing references, citations, and sources utilized in the article
• Distinguishing between opinion and objectively verifiable truths
• Checking for outdated, biased, or unbalanced information

If you identify factual errors, it’s vital to highlight them when critically analyzing the text. But remember, you could also (after careful scrutiny) also highlight that the text appears to be factually correct – that, too, is critical analysis.

8. Exploring Counterexamples

Exploring counterexamples involves searching and presenting instances or cases which contradict the arguments or conclusions presented in a text.

Counterexamples are an effective way to challenge the generalizations, assumptions or conclusions made in an article or theory. They can reveal weaknesses or oversights in the logic or validity of the author’s perspective.

Considerations in counterexample analysis are:

• Identifying generalizations made in the text
• Seeking examples in academic literature or real-world instances that contradict these generalizations
• Assessing the impact of these counterexamples on the validity of the text’s argument or conclusion

Exploring counterexamples enriches your critical analysis by injecting an extra layer of scrutiny, and even doubt, in the text.

By presenting counterexamples, you not only test the resilience and validity of the text but also open up new avenues of discussion and investigation that can further your understanding of the topic.

See Also: Counterargument Examples

9. Assessing Methodologies

Assessing methodologies entails examining the techniques, tools, or procedures employed by the author to collect, analyze and present their information.

The accuracy and validity of a text’s conclusions often depend on the credibility and appropriateness of the methodologies used.

Aspects to inspect include:

• The appropriateness of the research method for the research question
• The adequacy of the sample size
• The validity and reliability of data collection instruments
• The application of statistical tests and evaluations
• The implementation of controls to prevent bias or mitigate its impact

One strategy you could implement here is to consider a range of other methodologies the author could have used. If the author conducted interviews, consider questioning why they didn’t use broad surveys that could have presented more quantitative findings. If they only interviewed people with one perspective, consider questioning why they didn’t interview a wider variety of people, etc.

See Also: A List of Research Methodologies

10. Exploring Alternative Explanations

Exploring alternative explanations refers to the practice of proposing differing or opposing ideas to those put forward in the text.

An underlying assumption in any analysis is that there may be multiple valid perspectives on a single topic. The text you’re analyzing might provide one perspective, but your job is to bring into the light other reasonable explanations or interpretations.

Cultivating alternative explanations often involves:

• Formulating hypotheses or theories that differ from those presented in the text
• Referring to other established ideas or models that offer a differing viewpoint
• Suggesting a new or unique angle to interpret the data or phenomenon discussed in the text

Searching for alternative explanations challenges the authority of a singular narrative or perspective, fostering an environment ripe for intellectual discourse and critical thinking . It nudges you to examine the topic from multiple angles, enhancing your understanding and appreciation of the complexity inherent in the field.

A Full List of Critical Analysis Skills

• Exploring Strengths and Weaknesses
• Evaluating Sources
• Identifying Similarities
• Identifying Differences
• Identifying Biases
• Hypothesis Testing
• Fact-Checking
• Exploring Counterexamples
• Assessing Methodologies
• Exploring Alternative Explanations
• Pointing Out Contradictions
• Challenging the Significance
• Cause-And-Effect Analysis
• Assessing Generalizability
• Highlighting Inconsistencies
• Reductio ad Absurdum
• Comparing to Expert Testimony
• Comparing to Precedent
• Reframing the Argument
• Pointing Out Fallacies
• Questioning the Ethics
• Clarifying Definitions
• Challenging Assumptions
• Exposing Oversimplifications
• Highlighting Missing Information
• Demonstrating Irrelevance
• Assessing Effectiveness
• Assessing Trustworthiness
• Recognizing Patterns
• Differentiating Facts from Opinions
• Analyzing Perspectives
• Prioritization
• Making Predictions
• Conducting a SWOT Analysis
• PESTLE Analysis
• Asking the Five Whys
• Correlating Data Points
• Finding Anomalies Or Outliers
• Comparing to Expert Literature
• Drawing Inferences
• Assessing Validity & Reliability

Analysis and Bloom’s Taxonomy

Benjamin Bloom placed analysis as the third-highest form of thinking on his ladder of cognitive skills called Bloom’s Taxonomy .

This taxonomy starts with the lowest levels of thinking – remembering and understanding. The further we go up the ladder, the more we reach higher-order thinking skills that demonstrate depth of understanding and knowledge, as outlined below:

Here’s a full outline of the taxonomy in a table format:

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 5 Top Tips for Succeeding at University
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 50 Durable Goods Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 100 Consumer Goods Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 30 Globalization Pros and Cons

2 thoughts on “33 Critical Analysis Examples”

THANK YOU, THANK YOU, THANK YOU! – I cannot even being to explain how hard it has been to find a simple but in-depth understanding of what ‘Critical Analysis’ is. I have looked at over 10 different pages and went down so many rabbit holes but this is brilliant! I only skimmed through the article but it was already promising, I then went back and read it more in-depth, it just all clicked into place. So thank you again!

You’re welcome – so glad it was helpful.

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• Open access
• Published: 06 April 2016

How to review a case report

• Rakesh Garg 1 ,
• Shaheen E. Lakhan 2 &
• Ananda K. Dhanasekaran 3  

Journal of Medical Case Reports volume  10 , Article number:  88 ( 2016 ) Cite this article

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Peer Review reports

Introduction

Sharing individual patient experiences with clinical colleagues is an essential component of learning from each other. This sharing of information may be made global by reporting in a scientific journal. In medicine, patient management decisions are generally based on the evidence available for use of a particular investigation or technology [ 1 ]. The hierarchical rank of the evidence signifies the probability of bias. The higher up the hierarchy, the better its reliability and thus its clinical acceptance (Table  1 ). Though case reports remain lowest in the hierarchy of evidence, with meta-analysis representing the highest level, they nevertheless constitute important information with regard to rare events and may be considered as anecdotal evidence [ 2 ] (Table  1 ). Case reports may stimulate the generation of new hypotheses, and thus may support the emergence of new research.

The definition of a case report or a case series is not well defined in the literature and has been defined variously by different journals and authors. However, the basic definition of a case report is the detailed report of an individual including aspects like exposure, symptoms, signs, intervention, and outcome. It has been suggested that a report with more than four cases be called a case series and those with fewer than four a case report [ 3 ]. A case series is descriptive in design. Other authors describe “a collection of patients” as a case series and “a few patients” as a case report [ 4 ]. We suggest that should more than one case be reported, it may be defined as a case series—a concept proposed by other authors [ 5 ].

The importance of case reports

A case report may describe an unusual etiology, an unusual or unknown disorder, a challenging differential diagnosis, an unusual setting for care, information that can not be reproduced due to ethical reasons, unusual or puzzling clinical features, improved or unique technical procedures, unusual interactions, rare or novel adverse reactions to care, or new insight into the pathogenesis of disease [ 6 , 7 ]. In recent years, the publication of case reports has been given low priority by many high impact factor journals. However, the need for reporting such events remains. There are some journals dedicated purely to case reports, such as the Journal of Medical Case Reports , emphasizing their importance in modern literature. In the past, isolated case reports have led to significant advancements in patient care. For example, case reports concerning pulmonary hypertension and anorexic agents led to further trials and the identification of the mechanism and risk factors associated with these agents [ 2 , 8 ].

Reporting and publishing requirements

The reporting of cases varies for different journals. The authors need to follow the instructions for the intended publication. Owing to significant variability, it would be difficult to have uniform publication guidelines for case reports. A checklist called the CARE guidelines is useful for authors writing case reports [ 9 , 10 ]. However, it would be universally prudent to include a title, keywords, abstract, introduction, patient information, clinical findings, timeline, diagnostic assessment, therapeutic interventions, follow-up and outcomes, discussion, patient perspective, and informed consent.

Peer review process

The peer review process is an essential part of ethical and scientific writing. Peer review ultimately helps improve articles by providing valuable feedback to the author and helps editors make a decision regarding publication. The peer reviewer should provide unbiased, constructive feedback regarding the manuscript. They may also highlight the strengths and weaknesses of the report. When reviewing an article, it is prudent to read the entire manuscript first to understand the overall content and message. The reviewer than may read section-wise and provide comments to the authors and editorial team accordingly. The reviewer needs to consider the following important points when reviewing a case for possible publication [ 8 , 9 ] (summarized in Table  2 ).

Novelty remains the foremost important aspect of a case. The case report should introduce novel aspects of patient evaluation, investigation, treatment, or any other aspect related to patient care. The relevant information becomes a hypothesis generator for further study. The novelty may at times be balanced with some important information like severe adverse effects, even if they have been reported earlier. Reporting adverse events remains important so that information on cumulative adverse effects can be gathered globally, which helps in preparing a policy or guideline or a warning note for its use in patients. The data related to adverse effects include not only the impact but also the number of patients affected. This becomes more important for serious adverse effects. In the absence of an international registry for adverse effects, published case reports are important pieces of information. Owing to ethical concerns, formal evaluation may not be feasible in the format of prospective study.

Essential description

The case needs to have all essential details to allow a useful conclusion to emerge. For example, if a case is being reported for hemodynamic variability due to a drug, then the drug dose and timing along with timed vital signs need to be described.

Authenticity and genuineness

Honesty remains the most important basic principle of all publications. This remains a primary responsibility of the authors. However, if there is any doubt, reviewers may seek clarification. This doubt may result from some discordance in the case description. At times, a lack of correlation between the figures and description may act as “red flags.” For instance, authors may discuss a technique for dealing with a difficult airway, but the figure is of a normal-appearing airway. Another example would be where the data and figure do not correlate in a hemodynamic response related to a drug or a technique, with the graphical picture or screenshot of hemodynamics acting as an alert sign. Such cause for concern may be communicated in confidence to the editor.

Ethical or competing interests

Ethical issues need to be cautiously interpreted and communicated. The unethical use of a drug or device is not desirable and often unworthy of publication. This may relate to the route or dose of the drug administered. The off-label use of drugs where known side effects are greater than potential benefit needs to be discouraged and remains an example of unethical use. This use may be related to the drug dose, particularly when the drug dose exceeds the routine recommended dose, or to the route of administration. As an example, the maximal dose of acetaminophen (paracetamol) is 4g/day, and if an author reports exceeding this dose, it should be noted why a greater than recommended dose was used. Ultimately, the use of a drug or its route of administration needs to be justified in the manuscript. The reviewers need to serve as content experts regarding the drugs and other technologies used in the case. A literature search by the reviewer provides the data to comment on this aspect.

Competing interests (or conflicts of interest) are concerns that interfere or potentially interfere with presentation, review, or publication. They must be declared by the authors. Conflicts can relate to patient-related professional attributes (like the use of a particular procedure, drug, or instrument) being affected by some secondary gains (financial, non-financial, professional, personal). Financial conflict may be related to ownership, paid consultancy, patents, grants, honoraria, and gifts. Non-financial conflicts may be related to memberships, relationships, appearance as an expert witness, or personal convictions. At times, the conflict may be related to the author’s relationship with an organization or another person. A conflict may influence the interpretation of the outcome in an inappropriate and unscientific manner. Although conflicts may not be totally abolished, they must be disclosed when they reasonably exist. This disclosure should include information such as funding sources, present membership, and patents pending. Reviewers should cautiously interpret any potential bias regarding the outcome of the case based on the reported conflicts. This is essential for transparent reporting of research. At times, competing interests may be discovered by a reviewer and should be included in comments to the editorial team. Such conflicts may again be ascertained when the reviewer reviews the literature during the peer review process. The reviewer should also disclose their own conflicts related to the manuscript review when sending their report to the editorial team.

Impact on clinical practice

This is an important aspect for the final decision of whether to publish a case report. The main thrust or carry-home message needs to be emphasized clearly. It needs to be elaborated upon in concluding remarks.

Patient anonymity, consent, and ethical approval

When reviewing the manuscript of a case report, reviewers should ensure that the patient’s anonymity and confidentiality is protected. The reviewers should check that patient identifiers have been removed or masked from all aspects of the manuscript, whether in writing or within photograph. Identifiers can include things like the name of the patient, geographical location, date of birth, phone numbers, email of the patient, medical record numbers, or biometric identifiers. Utmost care needs to be taken to provide full anonymity for the patient.

Consent is required to participate in research, receive a certain treatment, and publish identifiable details. These consents are for different purposes and need to be explained separately to the patient. A patient’s consent to participate in the research or for use of the drug may not extend to consent for publication. All these aspects of consent must be explained to the patient, written explicitly in the patient’s own language, understood by the patient, and signed by the patient. For the purpose of the case, the patient must understand and consent for any new technique or drug (its dose, route, and timing) being used. In the case of a drug being used for a non-standard indication or route, consent for use must also be described. Patient consent is essential for the publication of a case if patient body parts are displayed in the article. This also includes any identifiers that can reveal the identity of the patient, such as the patient’s hospital identification number, address, and any other unique identifier. In situations where revealing the patient’s identity cannot be fully avoided, for example if the report requires an image of an identifiable body part like the face, then this should be explained to the patient, the image shown to them, and consent taken. Should the patient die, then consent must be obtained from next of kin or legal representative.

With case series, securing individual patient consent is advised and preferable. The authors may also need institutional review board (IRB) approval to publish a case series. IRBs can waive the need for consent if a study is conducted retrospectively and data are collected from patient notes for the purpose of research, usually in an anonymized way. However, wherever possible, individual patient consent is preferable, even for a retrospective study. Consent is mandatory for any prospective data collection for the purpose of publication as a case series. Consent and/or IRB approval must be disclosed in the case report and reasons for not obtaining individual consent may be described, if applicable.

There may be situations in which publishing patient details without their consent is justified, but this is a decision that should be made by the journal editor, who may decide to discuss the case with the Committee on Publication Ethics. Reviewers need to emphasize the issue to the editor when submitting their comments.

Manuscript writing

The CARE guidelines provide a framework that supports transparency and accuracy in the publication of case reports and the reporting of information from patient encounters. The acronym CARE was created from CA (the first two letters in “case”) and RE (the first two letters in “reports”). The initial CARE tools are the CARE checklist and the Case Report Writing Templates. These tools support the writing of case reports and provide data that inform clinical practice guidelines and provide early signals of effectiveness, harms, and cost [ 10 ].

The presentation of the case and its interpretation should be comprehensive and related. The various components of the manuscript should have sufficient information for understanding the key message of the case. The reviewer needs to comment on the relevant components of the manuscript. The reviewer should ascertain that the title of the case manuscript is relevant and includes keywords related to the case. The title should be short, descriptive, and interesting. The abstract should be brief, without any abbreviations, and include keywords. It is preferable to use Medical Subject Headings (MeSH) keywords. Reviewers must ensure that the introduction emphasizes the context of the case and describes the relevance and its importance in a concise and comprehensive manner. The case description should be complete and should follow basic rules of medical communication. The details regarding patient history, physical examination, investigations, differential diagnosis, management, and outcome should be described in chronological order. If repeated observations are present, then they may be tabulated. The use of graphs and figures helps the readers to better understand the case. Interpretation or inferences based on the outcomes should be avoided in this section and should be considered a part of the discussion. The discussion should highlight important aspects of the case, with its interpretation within the context of the available literature. References should be formatted as per the journal style. They should be complete and preferably of recent publications.

Reviewer responsibility

The reviewer’s remarks are essential not only for the editorial team but also for authors. A good peer review requires honesty, sincerity, and punctuality. Even if a manuscript is rejected, the authors should receive learning points from peer review commentary. The best way to review a manuscript is to read the manuscript in full for a gross overview and develop general comments. Thereafter, the reviewer should address each section of the manuscript separately and precisely. This may be done after a literature search if the reviewer needs to substantiate his/her commentary.

Constructive criticism

The reviewer’s remarks should be constructive to help the authors improve the manuscript for further consideration. If the manuscript is rejected, the authors should have a clear indication for the rejection. The remarks may be grouped as major and minor comments. Major comments likely suggest changes to the whole presentation, changing the primary aim of the case report, or adding images. Minor comments may include grammatical errors or getting references for a statement. The editorial team must be able to justify their decision on whether or not to accept an article for publication, often by citing peer review feedback. It is also good style to tabulate a list of the strengths and weaknesses of the manuscript.

Fixed time for review

Reviewer remarks should be submitted within a specified timeframe. If any delay is expected, it should be communicated to the editorial team. Reviewers should not rush to submit feedback without sufficient time to adequately review the paper and perform any necessary literature searches. Should a reviewer be unable to submit the review within the specified timeframe, they should reply to the review invitation to decline at their earliest convenience. If, after accepting a review invitation, the reviewer realizes they do not have time to perform the review, this must be communicated to the editorial team.

Conflict of interest

The reviewer’s conflicts of interest should be included along with the review. The conflicts may be related to the contents of the case, drugs, or devices pertaining to the case; the author(s); or the affiliated institution(s) of the author(s).

Lack of expertise

The reviewer may decline to review the manuscript if they think the topic is out of their area of expertise. If, after accepting an invitation to review, the reviewer realizes they are unable to review the manuscript owing to a lack of expertise in that particular field, they should disclose the fact to the editorial team.

Confidentiality

The reviewer should keep the manuscript confidential and should not use the contents of the unpublished manuscript in any form. Discussing the manuscript among colleagues or any scientific forum or meetings is inappropriate.

Review of revised manuscript

At times, a manuscript is sent for re-review to the reviewer. The reviewer should read the revised manuscript, the author’s response to the previous round of peer review, and the editorial comments. Sometimes, the authors may disagree with the reviewer’s remarks. This issue needs to be elaborated on and communicated with the editor. The reviewer should support their views with appropriate literature references. If the authors justify their reason for disagreeing with the viewer, then their argument should be considered evidence-based. However, if the reviewer still requests the revision, this may be politely communicated to the author and editor with justification for the same. In response to reviewers remarks, authors may not agree fully and provide certain suggestion in the form of clarification related to reviewers remarks. The reviewers should take these clarifications judiciously and comment accordingly with the intent of improving the manuscript further.

Peer reviewers have a significant role in the dissemination of scientific literature. They act as gatekeepers for science before it is released to society. Their sincerity and dedication is paramount to the success of any journal. The reviewers should follow a scientific and justifiable methodology for reviewing a case report for possible publication. Their comments should be constructive for the overall improvement of the manuscript and aid the editorial team in making a decision on publication. We hope this article will help reviewers to perform their important role in the best way possible. We send our best wishes to the reviewer community and, for those who are inspired to become reviewers after reading this article, our warm welcome to the reviewers’ club.

Burns PB, Rohrich RJ, Chung KC. The levels of evidence and their role in evidence-based medicine. Plast Reconstr Surg. 2011;128:305–10.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Green BN, Johnson CD. How to write a case report for publication. J Chiropr Med. 2006;5:72–82.

Article   PubMed   PubMed Central   Google Scholar  

Abu-Zidan FM, Abbas AK, Hefny AF. Clinical “case series”: a concept analysis. Afr Health Sci. 2012;12:557–62.

CAS   PubMed   PubMed Central   Google Scholar  

Porta M, editor. A dictionary of epidemiology/edited for the International Epidemiological Association. 5th ed. UK: Oxford University Press; 2008. p. 33.

Medical Research Council of South Africa. Evidence-based medicine. 2016. http://www.mrc.ac.za/healthsystems/sai.htm . Accessed on 1 Nov 2015.

Cohen H. How to write a patient case report. Am J Health-Syst Pharm. 2006;63:1888–92.

Article   PubMed   Google Scholar  

Roberts LW, Coverdale J, Edenharder K, Louie A. How to review a manuscript: a “down-to-earth” approach. Acad Psychiatry. 2004;28:81–7.

Rutowski JL, Cairone JV. How to review scientific manuscripts and clinical case reports for Journal of Oral Implantology. J Oral Implantol. 2009;35:310–4.

Article   Google Scholar  

Jabs DA. Improving the reporting of clinical case series. Am J Ophthalmol. 2005;139:900–5.

Gagnier JJ, Kienle G, Altman DG, Moher D, Sox H, Riley D; CARE Group. The CARE guidelines: consensus-based clinical case reporting guideline development. BMJ Case Reports. 2013; doi: 10.1136/bcr-2013-201554 .

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Department of Anaesthesiology, Pain and Palliative Care, DR BRAIRCH, AIIMS, Ansari Nagar, New Delhi, 110029, India

Rakesh Garg

Neurology and Medical Education, California University of Science and Medicine - School of Medicine, Colton, CA, USA

Shaheen E. Lakhan

Sandwell & West Birmingham Hospitals, NHS Trust, Birmingham, UK

Ananda K. Dhanasekaran

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Garg, R., Lakhan, S.E. & Dhanasekaran, A.K. How to review a case report. J Med Case Reports 10 , 88 (2016). https://doi.org/10.1186/s13256-016-0853-3

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Received : 27 August 2015

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DOI : https://doi.org/10.1186/s13256-016-0853-3

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Do Your Students Know How to Analyze a Case—Really?

Explore more.

• Case Teaching
• Student Engagement

J ust as actors, athletes, and musicians spend thousands of hours practicing their craft, business students benefit from practicing their critical-thinking and decision-making skills. Students, however, often have limited exposure to real-world problem-solving scenarios; they need more opportunities to practice tackling tough business problems and deciding on—and executing—the best solutions.

To ensure students have ample opportunity to develop these critical-thinking and decision-making skills, we believe business faculty should shift from teaching mostly principles and ideas to mostly applications and practices. And in doing so, they should emphasize the case method, which simulates real-world management challenges and opportunities for students.

To help educators facilitate this shift and help students get the most out of case-based learning, we have developed a framework for analyzing cases. We call it PACADI (Problem, Alternatives, Criteria, Analysis, Decision, Implementation); it can improve learning outcomes by helping students better solve and analyze business problems, make decisions, and develop and implement strategy. Here, we’ll explain why we developed this framework, how it works, and what makes it an effective learning tool.

The Case for Cases: Helping Students Think Critically

Business students must develop critical-thinking and analytical skills, which are essential to their ability to make good decisions in functional areas such as marketing, finance, operations, and information technology, as well as to understand the relationships among these functions. For example, the decisions a marketing manager must make include strategic planning (segments, products, and channels); execution (digital messaging, media, branding, budgets, and pricing); and operations (integrated communications and technologies), as well as how to implement decisions across functional areas.

Faculty can use many types of cases to help students develop these skills. These include the prototypical “paper cases”; live cases , which feature guest lecturers such as entrepreneurs or corporate leaders and on-site visits; and multimedia cases , which immerse students into real situations. Most cases feature an explicit or implicit decision that a protagonist—whether it is an individual, a group, or an organization—must make.

For students new to learning by the case method—and even for those with case experience—some common issues can emerge; these issues can sometimes be a barrier for educators looking to ensure the best possible outcomes in their case classrooms. Unsure of how to dig into case analysis on their own, students may turn to the internet or rely on former students for “answers” to assigned cases. Or, when assigned to provide answers to assignment questions in teams, students might take a divide-and-conquer approach but not take the time to regroup and provide answers that are consistent with one other.

To help address these issues, which we commonly experienced in our classes, we wanted to provide our students with a more structured approach for how they analyze cases—and to really think about making decisions from the protagonists’ point of view. We developed the PACADI framework to address this need.

PACADI: A Six-Step Decision-Making Approach

The PACADI framework is a six-step decision-making approach that can be used in lieu of traditional end-of-case questions. It offers a structured, integrated, and iterative process that requires students to analyze case information, apply business concepts to derive valuable insights, and develop recommendations based on these insights.

Prior to beginning a PACADI assessment, which we’ll outline here, students should first prepare a two-paragraph summary—a situation analysis—that highlights the key case facts. Then, we task students with providing a five-page PACADI case analysis (excluding appendices) based on the following six steps.

Step 1: Problem definition. What is the major challenge, problem, opportunity, or decision that has to be made? If there is more than one problem, choose the most important one. Often when solving the key problem, other issues will surface and be addressed. The problem statement may be framed as a question; for example, How can brand X improve market share among millennials in Canada? Usually the problem statement has to be re-written several times during the analysis of a case as students peel back the layers of symptoms or causation.

Step 2: Alternatives. Identify in detail the strategic alternatives to address the problem; three to five options generally work best. Alternatives should be mutually exclusive, realistic, creative, and feasible given the constraints of the situation. Doing nothing or delaying the decision to a later date are not considered acceptable alternatives.

Step 3: Criteria. What are the key decision criteria that will guide decision-making? In a marketing course, for example, these may include relevant marketing criteria such as segmentation, positioning, advertising and sales, distribution, and pricing. Financial criteria useful in evaluating the alternatives should be included—for example, income statement variables, customer lifetime value, payback, etc. Students must discuss their rationale for selecting the decision criteria and the weights and importance for each factor.

Step 4: Analysis. Provide an in-depth analysis of each alternative based on the criteria chosen in step three. Decision tables using criteria as columns and alternatives as rows can be helpful. The pros and cons of the various choices as well as the short- and long-term implications of each may be evaluated. Best, worst, and most likely scenarios can also be insightful.

Step 5: Decision. Students propose their solution to the problem. This decision is justified based on an in-depth analysis. Explain why the recommendation made is the best fit for the criteria.

Step 6: Implementation plan. Sound business decisions may fail due to poor execution. To enhance the likeliness of a successful project outcome, students describe the key steps (activities) to implement the recommendation, timetable, projected costs, expected competitive reaction, success metrics, and risks in the plan.

“Students note that using the PACADI framework yields ‘aha moments’—they learned something surprising in the case that led them to think differently about the problem and their proposed solution.”

PACADI’s Benefits: Meaningfully and Thoughtfully Applying Business Concepts

The PACADI framework covers all of the major elements of business decision-making, including implementation, which is often overlooked. By stepping through the whole framework, students apply relevant business concepts and solve management problems via a systematic, comprehensive approach; they’re far less likely to surface piecemeal responses.

As students explore each part of the framework, they may realize that they need to make changes to a previous step. For instance, when working on implementation, students may realize that the alternative they selected cannot be executed or will not be profitable, and thus need to rethink their decision. Or, they may discover that the criteria need to be revised since the list of decision factors they identified is incomplete (for example, the factors may explain key marketing concerns but fail to address relevant financial considerations) or is unrealistic (for example, they suggest a 25 percent increase in revenues without proposing an increased promotional budget).

In addition, the PACADI framework can be used alongside quantitative assignments, in-class exercises, and business and management simulations. The structured, multi-step decision framework encourages careful and sequential analysis to solve business problems. Incorporating PACADI as an overarching decision-making method across different projects will ultimately help students achieve desired learning outcomes. As a practical “beyond-the-classroom” tool, the PACADI framework is not a contrived course assignment; it reflects the decision-making approach that managers, executives, and entrepreneurs exercise daily. Case analysis introduces students to the real-world process of making business decisions quickly and correctly, often with limited information. This framework supplies an organized and disciplined process that students can readily defend in writing and in class discussions.

PACADI in Action: An Example

Here’s an example of how students used the PACADI framework for a recent case analysis on CVS, a large North American drugstore chain.

The CVS Prescription for Customer Value*

PACADI Stage

Summary Response

How should CVS Health evolve from the “drugstore of your neighborhood” to the “drugstore of your future”?

Alternatives

A1. Kaizen (continuous improvement)

A2. Product development

A3. Market development

A4. Personalization (micro-targeting)

Criteria (include weights)

C1. Customer value: service, quality, image, and price (40%)

C2. Customer obsession (20%)

C3. Growth through related businesses (20%)

C4. Customer retention and customer lifetime value (20%)

Each alternative was analyzed by each criterion using a Customer Value Assessment Tool

Alternative 4 (A4): Personalization was selected. This is operationalized via: segmentation—move toward segment-of-1 marketing; geodemographics and lifestyle emphasis; predictive data analysis; relationship marketing; people, principles, and supply chain management; and exceptional customer service.

Implementation

Partner with leading medical school

Curbside pick-up

Pet pharmacy

E-newsletter for customers and employees

Employee incentive program

CVS beauty days

Expand to Latin America and Caribbean

Healthier/happier corner

Holiday toy drives/community outreach

*Source: A. Weinstein, Y. Rodriguez, K. Sims, R. Vergara, “The CVS Prescription for Superior Customer Value—A Case Study,” Back to the Future: Revisiting the Foundations of Marketing from Society for Marketing Advances, West Palm Beach, FL (November 2, 2018).

Results of Using the PACADI Framework

When faculty members at our respective institutions at Nova Southeastern University (NSU) and the University of North Carolina Wilmington have used the PACADI framework, our classes have been more structured and engaging. Students vigorously debate each element of their decision and note that this framework yields an “aha moment”—they learned something surprising in the case that led them to think differently about the problem and their proposed solution.

These lively discussions enhance individual and collective learning. As one external metric of this improvement, we have observed a 2.5 percent increase in student case grade performance at NSU since this framework was introduced.

Tips to Get Started

The PACADI approach works well in in-person, online, and hybrid courses. This is particularly important as more universities have moved to remote learning options. Because students have varied educational and cultural backgrounds, work experience, and familiarity with case analysis, we recommend that faculty members have students work on their first case using this new framework in small teams (two or three students). Additional analyses should then be solo efforts.

To use PACADI effectively in your classroom, we suggest the following:

Advise your students that your course will stress critical thinking and decision-making skills, not just course concepts and theory.

Use a varied mix of case studies. As marketing professors, we often address consumer and business markets; goods, services, and digital commerce; domestic and global business; and small and large companies in a single MBA course.

As a starting point, provide a short explanation (about 20 to 30 minutes) of the PACADI framework with a focus on the conceptual elements. You can deliver this face to face or through videoconferencing.

Give students an opportunity to practice the case analysis methodology via an ungraded sample case study. Designate groups of five to seven students to discuss the case and the six steps in breakout sessions (in class or via Zoom).

Ensure case analyses are weighted heavily as a grading component. We suggest 30–50 percent of the overall course grade.

Once cases are graded, debrief with the class on what they did right and areas needing improvement (30- to 40-minute in-person or Zoom session).

Encourage faculty teams that teach common courses to build appropriate instructional materials, grading rubrics, videos, sample cases, and teaching notes.

When selecting case studies, we have found that the best ones for PACADI analyses are about 15 pages long and revolve around a focal management decision. This length provides adequate depth yet is not protracted. Some of our tested and favorite marketing cases include Brand W , Hubspot , Kraft Foods Canada , TRSB(A) , and Whiskey & Cheddar .

Art Weinstein , Ph.D., is a professor of marketing at Nova Southeastern University, Fort Lauderdale, Florida. He has published more than 80 scholarly articles and papers and eight books on customer-focused marketing strategy. His latest book is Superior Customer Value—Finding and Keeping Customers in the Now Economy . Dr. Weinstein has consulted for many leading technology and service companies.

Herbert V. Brotspies , D.B.A., is an adjunct professor of marketing at Nova Southeastern University. He has over 30 years’ experience as a vice president in marketing, strategic planning, and acquisitions for Fortune 50 consumer products companies working in the United States and internationally. His research interests include return on marketing investment, consumer behavior, business-to-business strategy, and strategic planning.

John T. Gironda , Ph.D., is an assistant professor of marketing at the University of North Carolina Wilmington. His research has been published in Industrial Marketing Management, Psychology & Marketing , and Journal of Marketing Management . He has also presented at major marketing conferences including the American Marketing Association, Academy of Marketing Science, and Society for Marketing Advances.

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Sample Case Analysis

This page shows a sample case analysis for the course  Genomics, Ethics, and Society .

Below is a "model" answer to the whitebark pine case . The case doesn't focus on genomics, but nonetheless, the way the model answer is laid out should help you to see what's being asked for. You should refer back to this model when you are writing up case studies of your own. While undergraduates should find this model useful, it's more like a graduate case study in terms of length and complexity. By a "model" answer, we don't mean that this answer is perfect; and obviously there's much more that could be said. But an answer with this kind of structure, content, and use of resources, would get a strong A.

When you analyse a case study, you're usually considering a complex situation where many different interests and values are at stake. This makes it easy to get tangled up in your answer too: so here's some tips for answering the case study well.

• Write a clear introduction in which you (a) identify what you are going to talk about (b) give some idea of how you are going to structure the paper by setting up "signposts"; and (c) outline what view or policy position you're going to argue for. (Usually case studies ask you to recommend a view, policy or position.) You may be able to say much more than you have room for; if so, be explicit at the beginning about what you're not discussing for space reasons, so the person grading knows you did think about it! 
• Stick to the structure you've outlined.
• In the course of analyzing the case, be sure to explain what values you think are at stake, where appropriate, who the stakeholders are, and why this case is likely to be contested.
• In some cases it may be useful to consider the perspectives of different stakeholders and different ethical theories: for instance, will someone who is worried about violating rights regard the ethical issues differently from someone who is concerned about maximizing overall good (say in terms of human welfare?)
• Where you use terms such as "liberty" "utilitarianism" "wildness" or "rights" make sure that you explain how you are using them as if to someone who is unfamiliar with the terms.
• Make an argument for which approach or approaches you think is/are best in the particular situation being described, and why. However, while doing so you should also explain the difficulties with the view for which you’re arguing, what someone might say who disagreed with the argument, and why their objection is not a good one/there’s a good response to it, etc. If you are really ambivalent about the case, say so and explain why.
• You should reference carefully, both in-text and in the reference section. If you quote or paraphrase anything, or you're dependent on a publication, you must provide an in-text reference. We don't mind what referencing system you use in your references, but your references should be detailed enough for us to find them (ie not just author and title).

Drawing on the whitebark pine case, here's just an example how you might find the ethics assessment process useful:

Ethics Assessment Process and the Whitebark Pine Case

1) seeing the problem.

What are the main ethical issues and conflicts presented in the case?

The case asks us to focus on the selection of rust-resistant strains and the assisted migration of WBP. While the selection of rust resistant strains doesn't raise all the ethical problems that GM does, it still means that there's enhanced human intervention and deliberate action involved in what trees end up existing (which may raise value questions about loss of wildness). Assisted migration raises a number of ethical issues and potential conflicts, primarily (a) the value of protecting a species from extinction (b) the possible ecological disvalues (and values) of deliberately introducing a species into a new area (c) the possible loss of wildness (d) cultural, historical and aesthetic values - could these be preserved? (e) questions about who owns the land where the trees would be moved (property rights, perhaps indigenous peoples, questions of environmental justice) and relevant consultative processes (f) potential effects on sentient animals, especially Clark’s Nutcrackers. From some ethical perspectives there could be "in principle" objections here. For instance, it might be argued that in principle humans shouldn't "interfere" in nature to move things, or that if moving WBP infringes on the rights of indigenous peoples, it is unethical in principle. On the other hand, an ethical approach that focuses on consequences will attempt to weigh and balance the values involved and make a decision based on what is likely to bring about the best outcome overall.

Who are the stakeholders and what are their respective positions? What decisions and/or impacts do they face?

Some of the issues here  involve very general groups of stakeholders: eg those who maintain that all species are valuable, so will want to protect the WBP; those who value the unusual aesthetics of the whitebark pine (these may be hikers and photographers) so may want it to be saved (this will depend on whether the aesthetic value is tied to current geographic location; if it is then moving it won’t save the value). It might be argued that future generations of humans are stakeholders; they would never get to see or enjoy landscapes created by this iconic species. More specific groups of stakeholders include:  biologists doing the research, both those working on genetic selection of the tree and those involved in planning assisted migration – they are likely to be in favor of both actions, and to see it as developing their research and conservation work. There are also likely to be biologists who oppose  all plans for assisted migration, primarily because they are concerned about moved organisms becoming invasive.  All those who generally oppose genetic selection of wild organisms are likely to oppose it in this case. Those who own/live near potential relocation sites have a clear stake in what may happen, though these individuals may be in favor of or opposed to the relocation, depending on the predicted ecological/cultural consequences of moving it and the forms of consultation involved. If sentient non-humans can be stakeholders, Clark’s Nutcrackers should be considered, but it’s difficult to make sense of what the relocation might mean for individual Clark’s Nutcrackers, since the relocation would not occur until the trees were mature enough to have seeds. The nutcrackers then moved will likely be harmed; but either they or their offspring may over time also be benefited. It could be argued by some that species themselves are stakeholders, though that view would be difficult to defend.

2) Empirical Issues

What empirical information is most important for addressing the main ethical questions?

What empirical facts are widely accepted, based on scientific evidence and peer review, about this issue? What empirical issues are contested or uncertain? How good is the information we have? Is it reliable?

Is there other information it would be useful to have? How could we go about obtaining this information? What should we check on or verify? Are there obvious ways of doing this?

There is some reasonably uncontested empirical information: that the WBP is threatened, that climate change means its climate envelope will move (though there is disagreement about the precision of climate models). Research suggests that rust resistant WBP is possible, and there are already strains of WBP in existence that are more resistant than others. The most important empirical information needed in terms of the relocation is: what are the ecological impacts of relocating likely to be? Also needed is empirical information about how people in recipient communities would regard the relocation. This information could be collected, though trial sites would take a long time to become established.

3) Conflicting Values

What values are at stake in the case?

Values at stake include:

• Wildness : (loss of wildness/naturalness in selecting strains; loss of wildness in human-caused relocation; possible loss of wildness in relocation site)
• Aesthetic value : whitebark pine has high aesthetic value
• Cultural/historical value:  the iconic value of the tree as a symbol of the harshness and challenges of the American West
• Justice : Might be a cause of procedural and distributional environmental injustice if transplanted onto indigenous lands without adequate consultation or against their will (or other private lands)
• Species values : If it’s thought that species have moral status, then causing extinction is wrong (and this is human-caused, even if not intentionally). On the other hand, if assisted migration of WBP threatened other species then assisted migration would be problematic for this reason.
• Suffering and welfare:  On many ethical views, suffering is a disvalue. If translocating Clark’s Nutcrackers causes them or individuals of other species suffering, that would be a problem. If translocating WBP provided habitat or food for other species eg individual bears and enhanced their welfare, that would be positive.

Which values have priority for which stakeholders?

Will particular decisions lead to the sacrifice of specific values? Is there any way of avoiding this?

Any decision here is going to involve the loss of wildness, which may be of concern to wilderness defenders – at least, those who value places fee of human influence. This wildness loss can’t be avoided. Any context-related value will be lost too, whatever is decided. It may be possible to avoid justice problems at the relocation site by adequate consultation & respect for local residents’ and indigenous peoples’ concerns and preferences. There may also be ways of minimizing suffering to Clark's nutcrackers, but this is likely to make the operation more expensive.  Not acting to save the WBP will involve loss of its aesthetic value for present and future generations.

4) Moral Imagination

Given the goals and objectives of the decision-makers, are there alternative courses of action that could be taken that fall outside the obvious parameters of this case? Can these be adopted without sacrificing any other goals or objectives?

When there are threats from climate change, organisms have to either adapt where they are or move. WBP additionally faces current problems from rust and beetles. Natural adaptation  in situ  alone is unlikely to happen, and moving the WBP without making it rust-resistant risks the same problems following it to the new location. And it’s unlikely the species will survive in its current locations, even if rust-resistant strains were introduced. So, the remaining alternative option (given that climate change is unlikely to stop) is just to let the tree become extinct and do nothing. This sacrifices species and aesthetic values, but is less ecologically risky in the reception ecosystem, is unlikely to cause new suffering (after all, the animals that lose WBP seeds for food in its current range will lose the seeds even if there is new WBP 600 miles north; and nutcrackers won’t have to be relocated) and avoids any justice concerns at the relocation site.

 5) Moral Justification

Among the available alternatives, which can be reasonably ethically defended?

Of the ethically defensible alternatives, is there one that's clearly the best? 

Both the main options (do nothing; move) can be ethically defended. For particular empirical reasons in this case, “move” may look best. However, judgment about this really depends on which values are prioritized and how precautionary you are.

6) Moral Criteria

Taking each alternative response to the case in turn (may not all be relevant to every case).

NB: In this case, whatever is done, some things are lost. For instance, those who value WBP as important cultural symbols of the American West, in their particular geographical locations, are going to lose this value whatever happens, since they can’t be preserved in their current location

Harm and Benefit :  Does this alternative cause harm? Does it cause less harm than the other alternatives? Does it bring about benefits?

• Do nothing:  Likely extinction of WBP. If species can be harmed, this causes species harm, but this argument is difficult to defend. If future people can be harmed, and if loss of a species can harm them, WBP extinction does harm them.
• Move without rust selection  This risks future harm to trees through WPBR and beetle, even in the new location. It’s possible that if ecosystems/species can be harmed that WBP in the new location could harm them (but there’s also a possibility of benefit). Possible harms to nutcrackers.
• Select and move :  Less risk of harm to trees in future. Small risk of harm to other species/systems from relocation. Also risk of harm to nutcrackers.

Justice : How does this alternative distribute harms and benefits or other natural and social goods? Are those affected meaningfully involved in decision-making?

• Do nothing : The species going extinct may affect some people’s interests, but it’s not really an injustice. It would be difficult to consult about not saving the tree, other than by surveys.
• Move (select or not) : The main location of a possible injustice to people lies in the move to new habitat without consultation or against the will of those who live there or own the land.

Other human values : Does this alternative have significant impacts on privacy, liberty, or other human values?

Moving could impact on property rights.

Environmental values : Does this alternative have significant impact on the non-human world?

All options have significant impacts on the non-human world, either by letting a species go extinct, or by selecting forms resistant to disease/ moving them to a new ecosystem. This is really a case where different environmental values are in conflict AND sometimes the same values are in conflict (eg moving WBP may save one species and threaten others, may protect one aesthetic value while changing another etc)

Ethical theories : What might different ethical theories say about what should be done?

• Consequentialist approaches will sum values; what values count will depend on the approach. Utilitarians, for instance, will sum pleasure net of pain over time; this will include humans and sentient animals. So the impacts gains/losses of values on human happiness will matter; so also impacts on Clark’s nutcrackers and other animals that use WBP for food or habitat.
• Rights theories: Relocation, if not handled appropriately, could violate property rights, or the rights of indigenous peoples to self-determination over their own land. If animals have rights, relocation of Clark’s nutcrackers, if this constituted a serious harm to individual birds, would violate their rights. If rights are regarded as inviolable or virtually inviolable, these hurdles would have to be overcome for the relocation to be ethically permissible. If it could be argued that species have rights (which is doubtful) then the WBP might be argued to have a compensatory “right” to relocation, since humans are in part at least responsible for their being endangered.
• Virtue theory: As this is primarily a policy issue rather than a personal or professional issue, virtue theory is less helpful in thinking about this case.

7) Other Criteria

Practicality : Are specific alternatives really feasible?

All the considered alternatives are at least plausible. The relocation has had trials and is short-term successful (over a couple of years); selected rust resistance is currently being trialed. There may be hurdles to both, but not evident at the moment.

Publicity : How would the public react to different alternatives?

Reactions will be mixed. Some will want to save the species. Others will regard the relocation as unacceptable interference in "nature" or the wild, with potentially bad consequences.

Collegiality : How would one's peers react to different alternatives?

Not so relevant here.

Reversibility : Can a decision made be revisited?

If the tree goes extinct, while de-extinction is perhaps possible, it’s unlikely. If it’s relocated, and proves to be invasive, it’s easy to remove (slow growing, slow to reproductively mature, easy to locate, needs nutcrackers). It seems likely that most of the potential ecological harms of any move could be reversed.

Continue to Sample Case Response

NB: The case study and case analysis here draws on: Palmer, C. & Larson, B. 2014. "Should we move the Whitebark Pine?"  Environmental Values  23: 641-662.

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This material is based upon work supported by the National Science Foundation under Award No. 2055332. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Data Analytics Case Study Guide 2024

by Sam McKay, CFA | Data Analytics

Data analytics case studies reveal how businesses harness data for informed decisions and growth.

For aspiring data professionals, mastering the case study process will enhance your skills and increase your career prospects.

So, how do you approach a case study?

Use these steps to process a data analytics case study:

Understand the Problem: Grasp the core problem or question addressed in the case study.

Collect Relevant Data: Gather data from diverse sources, ensuring accuracy and completeness.

Apply Analytical Techniques: Use appropriate methods aligned with the problem statement.

Visualize Insights: Utilize visual aids to showcase patterns and key findings.

Derive Actionable Insights: Focus on deriving meaningful actions from the analysis.

This article will give you detailed steps to navigate a case study effectively and understand how it works in real-world situations.

By the end of the article, you will be better equipped to approach a data analytics case study, strengthening your analytical prowess and practical application skills.

Let’s dive in!

Table of Contents

What is a Data Analytics Case Study?

A data analytics case study is a real or hypothetical scenario where analytics techniques are applied to solve a specific problem or explore a particular question.

It’s a practical approach that uses data analytics methods, assisting in deciphering data for meaningful insights. This structured method helps individuals or organizations make sense of data effectively.

Additionally, it’s a way to learn by doing, where there’s no single right or wrong answer in how you analyze the data.

So, what are the components of a case study?

Key Components of a Data Analytics Case Study

A data analytics case study comprises essential elements that structure the analytical journey:

Problem Context: A case study begins with a defined problem or question. It provides the context for the data analysis , setting the stage for exploration and investigation.

Data Collection and Sources: It involves gathering relevant data from various sources , ensuring data accuracy, completeness, and relevance to the problem at hand.

Analysis Techniques: Case studies employ different analytical methods, such as statistical analysis, machine learning algorithms, or visualization tools, to derive meaningful conclusions from the collected data.

Insights and Recommendations: The ultimate goal is to extract actionable insights from the analyzed data, offering recommendations or solutions that address the initial problem or question.

Now that you have a better understanding of what a data analytics case study is, let’s talk about why we need and use them.

Why Case Studies are Integral to Data Analytics

Case studies serve as invaluable tools in the realm of data analytics, offering multifaceted benefits that bolster an analyst’s proficiency and impact:

Real-Life Insights and Skill Enhancement: Examining case studies provides practical, real-life examples that expand knowledge and refine skills. These examples offer insights into diverse scenarios, aiding in a data analyst’s growth and expertise development.

Validation and Refinement of Analyses: Case studies demonstrate the effectiveness of data-driven decisions across industries, providing validation for analytical approaches. They showcase how organizations benefit from data analytics. Also, this helps in refining one’s own methodologies

Showcasing Data Impact on Business Outcomes: These studies show how data analytics directly affects business results, like increasing revenue, reducing costs, or delivering other measurable advantages. Understanding these impacts helps articulate the value of data analytics to stakeholders and decision-makers.

Learning from Successes and Failures: By exploring a case study, analysts glean insights from others’ successes and failures, acquiring new strategies and best practices. This learning experience facilitates professional growth and the adoption of innovative approaches within their own data analytics work.

Including case studies in a data analyst’s toolkit helps gain more knowledge, improve skills, and understand how data analytics affects different industries.

Using these real-life examples boosts confidence and success, guiding analysts to make better and more impactful decisions in their organizations.

But not all case studies are the same.

Let’s talk about the different types.

Types of Data Analytics Case Studies

Data analytics encompasses various approaches tailored to different analytical goals:

Exploratory Case Study: These involve delving into new datasets to uncover hidden patterns and relationships, often without a predefined hypothesis. They aim to gain insights and generate hypotheses for further investigation.

Predictive Case Study: These utilize historical data to forecast future trends, behaviors, or outcomes. By applying predictive models, they help anticipate potential scenarios or developments.

Diagnostic Case Study: This type focuses on understanding the root causes or reasons behind specific events or trends observed in the data. It digs deep into the data to provide explanations for occurrences.

Prescriptive Case Study: This case study goes beyond analytics; it provides actionable recommendations or strategies derived from the analyzed data. They guide decision-making processes by suggesting optimal courses of action based on insights gained.

Each type has a specific role in using data to find important insights, helping in decision-making, and solving problems in various situations.

Regardless of the type of case study you encounter, here are some steps to help you process them.

Roadmap to Handling a Data Analysis Case Study

Embarking on a data analytics case study requires a systematic approach, step-by-step, to derive valuable insights effectively.

Here are the steps to help you through the process:

Step 1: Understanding the Case Study Context: Immerse yourself in the intricacies of the case study. Delve into the industry context, understanding its nuances, challenges, and opportunities.

Identify the central problem or question the study aims to address. Clarify the objectives and expected outcomes, ensuring a clear understanding before diving into data analytics.

Step 2: Data Collection and Validation: Gather data from diverse sources relevant to the case study. Prioritize accuracy, completeness, and reliability during data collection. Conduct thorough validation processes to rectify inconsistencies, ensuring high-quality and trustworthy data for subsequent analysis.

Step 3: Problem Definition and Scope: Define the problem statement precisely. Articulate the objectives and limitations that shape the scope of your analysis. Identify influential variables and constraints, providing a focused framework to guide your exploration.

Step 4: Exploratory Data Analysis (EDA): Leverage exploratory techniques to gain initial insights. Visualize data distributions, patterns, and correlations, fostering a deeper understanding of the dataset. These explorations serve as a foundation for more nuanced analysis.

Step 5: Data Preprocessing and Transformation: Cleanse and preprocess the data to eliminate noise, handle missing values, and ensure consistency. Transform data formats or scales as required, preparing the dataset for further analysis.

Step 6: Data Modeling and Method Selection: Select analytical models aligning with the case study’s problem, employing statistical techniques, machine learning algorithms, or tailored predictive models.

In this phase, it’s important to develop data modeling skills. This helps create visuals of complex systems using organized data, which helps solve business problems more effectively.

Understand key data modeling concepts, utilize essential tools like SQL for database interaction, and practice building models from real-world scenarios.

Furthermore, strengthen data cleaning skills for accurate datasets, and stay updated with industry trends to ensure relevance.

Step 7: Model Evaluation and Refinement: Evaluate the performance of applied models rigorously. Iterate and refine models to enhance accuracy and reliability, ensuring alignment with the objectives and expected outcomes.

Step 8: Deriving Insights and Recommendations: Extract actionable insights from the analyzed data. Develop well-structured recommendations or solutions based on the insights uncovered, addressing the core problem or question effectively.

Step 9: Communicating Results Effectively: Present findings, insights, and recommendations clearly and concisely. Utilize visualizations and storytelling techniques to convey complex information compellingly, ensuring comprehension by stakeholders.

Step 10: Reflection and Iteration: Reflect on the entire analysis process and outcomes. Identify potential improvements and lessons learned. Embrace an iterative approach, refining methodologies for continuous enhancement and future analyses.

This step-by-step roadmap provides a structured framework for thorough and effective handling of a data analytics case study.

Now, after handling data analytics comes a crucial step; presenting the case study.

Presenting Your Data Analytics Case Study

Presenting a data analytics case study is a vital part of the process. When presenting your case study, clarity and organization are paramount.

To achieve this, follow these key steps:

Structuring Your Case Study: Start by outlining relevant and accurate main points. Ensure these points align with the problem addressed and the methodologies used in your analysis.

Crafting a Narrative with Data: Start with a brief overview of the issue, then explain your method and steps, covering data collection, cleaning, stats, and advanced modeling.

Visual Representation for Clarity: Utilize various visual aids—tables, graphs, and charts—to illustrate patterns, trends, and insights. Ensure these visuals are easy to comprehend and seamlessly support your narrative.

Highlighting Key Information: Use bullet points to emphasize essential information, maintaining clarity and allowing the audience to grasp key takeaways effortlessly. Bold key terms or phrases to draw attention and reinforce important points.

Addressing Audience Queries: Anticipate and be ready to answer audience questions regarding methods, assumptions, and results. Demonstrating a profound understanding of your analysis instills confidence in your work.

Integrity and Confidence in Delivery: Maintain a neutral tone and avoid exaggerated claims about findings. Present your case study with integrity, clarity, and confidence to ensure the audience appreciates and comprehends the significance of your work.

By organizing your presentation well, telling a clear story through your analysis, and using visuals wisely, you can effectively share your data analytics case study.

This method helps people understand better, stay engaged, and draw valuable conclusions from your work.

We hope by now, you are feeling very confident processing a case study. But with any process, there are challenges you may encounter.

Key Challenges in Data Analytics Case Studies

A data analytics case study can present various hurdles that necessitate strategic approaches for successful navigation:

Challenge 1: Data Quality and Consistency

Challenge: Inconsistent or poor-quality data can impede analysis, leading to erroneous insights and flawed conclusions.

Solution: Implement rigorous data validation processes, ensuring accuracy, completeness, and reliability. Employ data cleansing techniques to rectify inconsistencies and enhance overall data quality.

Challenge 2: Complexity and Scale of Data

Challenge: Managing vast volumes of data with diverse formats and complexities poses analytical challenges.

Solution: Utilize scalable data processing frameworks and tools capable of handling diverse data types. Implement efficient data storage and retrieval systems to manage large-scale datasets effectively.

Challenge 3: Interpretation and Contextual Understanding

Challenge: Interpreting data without contextual understanding or domain expertise can lead to misinterpretations.

Solution: Collaborate with domain experts to contextualize data and derive relevant insights. Invest in understanding the nuances of the industry or domain under analysis to ensure accurate interpretations.

Challenge 4: Privacy and Ethical Concerns

Challenge: Balancing data access for analysis while respecting privacy and ethical boundaries poses a challenge.

Solution: Implement robust data governance frameworks that prioritize data privacy and ethical considerations. Ensure compliance with regulatory standards and ethical guidelines throughout the analysis process.

Challenge 5: Resource Limitations and Time Constraints

Challenge: Limited resources and time constraints hinder comprehensive analysis and exhaustive data exploration.

Solution: Prioritize key objectives and allocate resources efficiently. Employ agile methodologies to iteratively analyze and derive insights, focusing on the most impactful aspects within the given timeframe.

Recognizing these challenges is key; it helps data analysts adopt proactive strategies to mitigate obstacles. This enhances the effectiveness and reliability of insights derived from a data analytics case study.

Now, let’s talk about the best software tools you should use when working with case studies.

Top 5 Software Tools for Case Studies

In the realm of case studies within data analytics, leveraging the right software tools is essential.

Here are some top-notch options:

Tableau : Renowned for its data visualization prowess, Tableau transforms raw data into interactive, visually compelling representations, ideal for presenting insights within a case study.

Python and R Libraries: These flexible programming languages provide many tools for handling data, doing statistics, and working with machine learning, meeting various needs in case studies.

Microsoft Excel : A staple tool for data analytics, Excel provides a user-friendly interface for basic analytics, making it useful for initial data exploration in a case study.

SQL Databases : Structured Query Language (SQL) databases assist in managing and querying large datasets, essential for organizing case study data effectively.

Statistical Software (e.g., SPSS , SAS ): Specialized statistical software enables in-depth statistical analysis, aiding in deriving precise insights from case study data.

Choosing the best mix of these tools, tailored to each case study’s needs, greatly boosts analytical abilities and results in data analytics.

Final Thoughts

Case studies in data analytics are helpful guides. They give real-world insights, improve skills, and show how data-driven decisions work.

Using case studies helps analysts learn, be creative, and make essential decisions confidently in their data work.

Check out our latest clip below to further your learning!

Frequently Asked Questions

What are the key steps to analyzing a data analytics case study.

When analyzing a case study, you should follow these steps:

Clarify the problem : Ensure you thoroughly understand the problem statement and the scope of the analysis.

Make assumptions : Define your assumptions to establish a feasible framework for analyzing the case.

Gather context : Acquire relevant information and context to support your analysis.

Analyze the data : Perform calculations, create visualizations, and conduct statistical analysis on the data.

Provide insights : Draw conclusions and develop actionable insights based on your analysis.

How can you effectively interpret results during a data scientist case study job interview?

During your next data science interview, interpret case study results succinctly and clearly. Utilize visual aids and numerical data to bolster your explanations, ensuring comprehension.

Frame the results in an audience-friendly manner, emphasizing relevance. Concentrate on deriving insights and actionable steps from the outcomes.

How do you showcase your data analyst skills in a project?

To demonstrate your skills effectively, consider these essential steps. Begin by selecting a problem that allows you to exhibit your capacity to handle real-world challenges through analysis.

Methodically document each phase, encompassing data cleaning, visualization, statistical analysis, and the interpretation of findings.

Utilize descriptive analysis techniques and effectively communicate your insights using clear visual aids and straightforward language. Ensure your project code is well-structured, with detailed comments and documentation, showcasing your proficiency in handling data in an organized manner.

Lastly, emphasize your expertise in SQL queries, programming languages, and various analytics tools throughout the project. These steps collectively highlight your competence and proficiency as a skilled data analyst, demonstrating your capabilities within the project.

Can you provide an example of a successful data analytics project using key metrics?

A prime illustration is utilizing analytics in healthcare to forecast hospital readmissions. Analysts leverage electronic health records, patient demographics, and clinical data to identify high-risk individuals.

Implementing preventive measures based on these key metrics helps curtail readmission rates, enhancing patient outcomes and cutting healthcare expenses.

This demonstrates how data analytics, driven by metrics, effectively tackles real-world challenges, yielding impactful solutions.

Why would a company invest in data analytics?

Companies invest in data analytics to gain valuable insights, enabling informed decision-making and strategic planning. This investment helps optimize operations, understand customer behavior, and stay competitive in their industry.

Ultimately, leveraging data analytics empowers companies to make smarter, data-driven choices, leading to enhanced efficiency, innovation, and growth.

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• Open access
• Published: 25 April 2024

A framework for the analysis of historical newsreels

• Mila Oiva   ORCID: orcid.org/0000-0002-5241-7436 1 ,
• Ksenia Mukhina 1 ,
• Vejune Zemaityte   ORCID: orcid.org/0000-0001-9714-7903 1 ,
• Andres Karjus   ORCID: orcid.org/0000-0002-2445-5072 1 , 2 ,
• Mikhail Tamm 1 ,
• Tillmann Ohm 1 ,
• Mark Mets 1 ,
• Daniel Chávez Heras   ORCID: orcid.org/0000-0002-9877-7496 3 ,
• Mar Canet Sola   ORCID: orcid.org/0000-0001-5986-3239 1 ,
• Helena Hanna Juht 4 &
• Maximilian Schich 1  

Humanities and Social Sciences Communications volume  11 , Article number:  530 ( 2024 ) Cite this article

Metrics details

• Cultural and media studies

Audiovisual news is a critical cultural phenomenon that has been influencing audience worldviews for more than a hundred years. To understand historical trends in multimodal audiovisual news, we need to explore them longitudinally using large sets of data. Despite promising developments in film history, computational video analysis, and other relevant fields, current research streams have limitations related to the scope of data used, the systematism of analysis, and the modalities and elements to be studied in audiovisual material and its metadata. Simultaneously, each disciplinary approach contributes significant input to research reducing these limitations. We therefore advocate for combining the strengths of several disciplines. Here we propose a multidisciplinary framework for systematically studying large collections of historical audiovisual news to gain a coherent picture of their temporal dynamics, cultural diversity, and potential societal effects across several quantitative and qualitative dimensions of analysis. By using newsreels as an example of such complex historically formed data, we combine the context crucial to qualitative approaches with the systematicity and ability to cover large amounts of data from quantitative methods. The framework template for historical newsreels is exemplified by a case study of the “News of the Day” newsreel series produced in the Soviet Union during 1944–1992. The proposed framework enables a more nuanced analysis of longitudinal collections of audiovisual news, expanding our understanding of the dynamics of global knowledge cultures.

Introduction

Audiovisual news has affected the global knowledge landscape for over a century. As a media format, audiovisual is impactful, and news as a genre is particularly effective for forming knowledge about the world. Although what counts as news is debatable (Tworek, 2019 ), labelling a story as ‘news’ suggests that the offered content has contemporary relevance and that it provides truthful information on the surrounding world—even if we know that this is not always the case (Winston, 2018 ; Lazer et al., 2018 ). Understanding audiovisual news content is crucial because news, taking part in creating the ‘media reality’ (Morgan, 2008 ), steers our gaze to the world, affects our opinions, and shapes our identities (Imesch et al., 2016 ; Hoffmann, 2018 ; Werenskjold, 2018 ). Even if some audiences may disagree with the content (Sampaio, 2022 ), news sets the agenda for societal discussions and contributes to what we consider worth knowing.

To fully understand the functions of audiovisual news content, production, and dissemination, exploring them through large and consistent sets of data, covering a long time span, can be helpful. Examining a consistent set of data that, for example, covers all the issues of a newsreel series, gives an understanding of the variety of individual findings and contextualises them. Detecting long-term continuities, and short-term trends helps us better understand the past information culture, alongside what is perhaps specific to our time or area. However, so far, studying audiovisual news via large quantities of data or across a long time span systematically in ways that would take into account their complexity has been hampered by availability of data and integration of methods across disciplines. Here we work towards a unified approach to study audiovisual news that enables the comparison of data coming from different sources to reveal the cultural and temporal variations of the global news scene.

Newsreels were the first widely spread form of audiovisual news. Starting in France in 1909, these approximately ten-minute-long news films, shown in the weekly changing series in cinemas, informed audiences about the latest political events, innovations, sports competitions, and fashion trends. Each newsreel issue contained around five to twelve short news stories, often showing the ‘more serious’ ones first and ending with entertaining topics. Until the mid-1950s, newsreels were the main source of audiovisual news for audiences globally that also conveyed both political propaganda and commercial interests. Their production continued in some countries under state support until the 1990s (Chambers et al., 2018 ; Pozharliev and Gallo González, 2018 ; Fielding, 2009 ).

Like other audiovisual products, newsreels are multifaceted. They are multimodal combinations of moving images, sounds, music, and of spoken and written language, gestures, iconographies, and signs as deeply rooted in the surrounding societies. The meanings created are interrelated across modalities with an individual news story gaining additional meaning, depending on its embedding and temporal position in a newsreel issue. In fact, one may argue, the meaning of a newsreel issue can be understood only when looking at the contents of the other issues of the newsreel series. Therefore, in order to understand the messages and role of individual news stories in a society, it is necessary to study newsreels as a whole (Hickethier, 2016 ) and comparatively, systematically analysing larger collections through the interconnections of small-scale units. This, we argue, has to transcend the debate of a single community of practice, such as media studies or communication, which is why this paper brings forth the expertise from a broad range of research streams—including film history, computational video analysis, film studies, and the so-called New Cinema History—to study film and video in a comprehensive way.

Lately, many newsreel series have been digitised, and several national film archives as well as transnational collections, such as Europeana, the Internet Archive, and Wikimedia Commons, all increasingly provide access to newsreels in digital form. This has opened new possibilities for studying long-term patterns of audiovisual news. However, despite promising developments in various disciplines, current approaches to newsreels, as discussed below, do not allow us to fully grasp these complex cultural products. Many established research fields are relevant to the longitudinal study of historical newsreels and audiovisual news in general. However, if the current approaches from each research stream are used separately, they produce considerable gaps in the nuanced understanding of newsreels in a long temporal continuum. The available approaches are either qualitative and do not allow a systematic analysis of large-scale data, or quantitative and reveal only one aspect of the multimodal newsreel data. Table 1 summarises the related research streams and their gaps, ranging from the scope of data used, comparability of analysis, the modalities taken into account, and the elements creating meaning in audiovisual material. Simultaneously, each research stream offers a contribution that helps fill the gaps in other fields. In the following paragraphs, we elaborate further on the gaps in each of these research streams together with the beneficial contributions that they may bring.

Qualitative film history

Qualitative film historical studies on newsreels have been demonstrating the variety of production conditions, core messages, and distribution channels in a number of countries and at different times (Chambers et al., 2018 ; Garrett Cooper et al., 2018 ; Imesch et al., 2016 ). Their strength is that they take into account the interplay of multiple modalities in the film material and produce nuanced analyses of the messages they have conveyed to the audiences. Simultaneously, however, they focus on temporally restricted segments of data, use analysis methods that are hard to apply to a large quantities of data, and do not usually utilise categories that would allow systematic comparisons between different studies (Chambers, 2018 , Pozharliev and Gallo González, 2018 , Bergström and Jönsson, 2018 , Vande Winkel and Biltereyst, 2018 ; Pozdorovkin, 2012 , Veldi et al., 2019 ). The main limitation of qualitative enquiry is its incomplete ability to offer an understanding of what is prevailing and what is marginal in wider terms in the data, which makes it difficult to see the bigger picture and contextualise the findings. As van Noord ( 2022 ) notes, exploring recurring motifs or patterns in cultural data is crucial for a deeper understanding. Although an experienced qualitative scholar is usually able to point out some of the repeating patterns based on their accumulated knowledge of the field, computational methods can back that up, measure the prevalence of the pattern in the collection, and detect also other, possibly unnoticed patterns.

Computational video analysis

Computational video analysis focuses on the systematic study of large collections of data, while typically addressing a single modality rather than aggregates of contextual and temporal factors. Examples include increasingly accurate and effective methods for recognising shot and scene boundaries (Hanjalic, 2002 ; Rasheed and Shah, 2003 ), persons (Wang and Zhang, 2022 ), objects (Brasó et al., 2022 ), human poses (Broadwell and Tangherlini, 2021 ), number of individuals in a crowd (Zhang and Chan, 2022 ), events (Wan et al., 2021 ), sounds (Park et al., 2021 ), human and animal behaviour (Gulshad et al., 2023 ; Bain et al., 2021 ; Sommer et al., 2020 ) and to perform image segmentation (Hu et al., 2022 ). Different solutions for condensing audiovisual content have also been developed, either for creating video representations to enable efficient browsing (Zhao et al., 2021 ) or numerical fingerprints allowing comparisons of video content for retrieval and recommendation systems (Kordopatis-Zilos et al., 2022 ; Nazir et al., 2020 ). Deep Learning applications in computer vision have been used for various item recognition tasks in images and videos (Bhargav et al., 2019 ; Liu et al., 2020 ; Kong and Fu, 2022 ; Brissman et al., 2022 ; Kandukuri et al., 2022 ). While mainstream computational video content analysis has focused on images, other modalities, like sound, have been also gaining increased attention (Valverde et al., 2021 ; Yang et al., 2020 ; Senocak et al., 2018 ; Hasegawa and Kato, 2019 ; Hu et al., 2022 ; Ye and Kovashka, 2022 ; Sanguineti et al., 2022 ; Pérez et al., 2020 ), eventually feeding into multi-modal analysis (Mourchid et al., 2019 ; Ren et al., 2018 ). However, considering different modalities of audiovisual data, particularly within the historical focus of this paper, remains beyond mainstream in video analysis. In addition, there is a lack of discussion on how certain units of analysis, such as recognised objects or condensed forms of video content, can be credibly used to detect the ways audiovisual content creates and conveys meaning to audiences.

Computational film studies

Situated between the qualitative and quantitative study of audiovisual contents, computational film studies often combine the two approaches. This stream of literature started by using shot detection to analyse film dynamics and editing styles (Salt, 1974 ; Tsivian, 2009 ; Pustu-Iren et al., 2020 ). In addition to addressing dynamics as an important modality of audiovisual content, computational film scholars have also been combining different modalities, such as images and sound (Grósz et al., 2022 ), spoken texts (Carrive et al., 2021 ; van Noord et al., 2021 ), or shown locations (Olesen et al., 2016 ). Computational studies of newsreels more specifically have addressed the contents of news either on the level of textual descriptions of news story topics (Althaus et al., 2018 ; Althaus and Britzman, 2018 ) or at a more granular level combining different modalities by analysing the voice-over text and automatically recognising well-known individuals in the film material (Carrive et al., 2021 ).

An ongoing debate in computational film studies concerns how film creates meaning, what are the most important meaning-making units, and how they could be best extracted (Chávez Heras, 2024 ; Burghardt et al., 2020 ; Burges et al., 2021 ). A profound challenge is that many modalities of film, such as images, can be interpreted in divergent ways depending on the viewer and their context (van Noord, 2022 ; Arnold and Tilton, 2019 ; Pozdorovkin, 2012 ). Different modalities may also create juxtaposing messages (Pozharliev and Gallo González, 2018 ). David Bordwell ( 1991 ) has argued that films contain ‘cues’ on which the further comprehension and interpretation of their meaning is based. Although the spectators may have differing opinions on the profound message of a film, an important hypothesis is that they nevertheless usually agree upon what the meaning-making cues are (such as shown activities or spoken sentences). This means that the variety of “credible” interpretations of the message of the film is limited (Bordwell, 1991 ). A central premise of computational film studies is thus that it can be possible to detect these cues and reach for an aggregate meaning of films through them.

Lately, in pursuit of understanding the meanings carried by film, a number of scholars have been using recognition and annotation of pre-set categories or stylistic features, discussing whether human interpretation should be applied already at the event of recognising the items, or at a later stage of the analysis (Carrive et al., 2021 ; Bhargav et al., 2019 ; Heftberger, 2018 ; Burges et al., 2021 ; Williams and Bell, 2021 ; Hielscher, 2020 ; Cooper et al., 2021 ; Bakels et al., 2020 ; authors discussing this issue: Burghardt et al., 2020 ; Arnold et al., 2021 ; Masson et al., 2020 ). There are also scholars further problematising object recognition by stating that in addition to recognising an object we should know how it is portrayed in order to understand its meaning (Hielscher, 2020 ) and calling for more thorough thinking of which measures can be used to analyse film contents (Olesen and Kisjes, 2018 ). This discussion connects with the wider question if there are cues in film that create meaning, how to find them, how to decide what to measure, and how to make sure that what is being measured gives responses to salient research questions. Although computational studies of historical newsreels use elaborate methods (Carrive et al., 2021 ; Althaus et al., 2018 ; Althaus and Britzman, 2018 ) including more explicit discussion on the connection of the research question and the variables can be an important methodological amendment to research.

New cinema history

New Cinema History (Maltby et al., 2011 ) stresses the importance of societal and temporal context in recent studies on film production (Dang, 2020 ), circulation (Clariana-Rodagut and Hagener, 2023 ; van Oort et al., 2020 ; Verhoeven et al., 2019 ; Navitski and Poppe, 2017 ), and reception (Treveri Gennari and Sedgwick, 2022 ). The premise of this discipline is that alongside the content, the surrounding context and its change over time are crucial factors in creating the meaning of film (as also pointed out by van Noord et al., 2022 ). Focusing on the contextual factors, this research stream has dealt less with content, yet because the meaning of cultural artefacts relies on both, these aspects need to be combined to reach a more nuanced understanding of newsreels or their aggregated meaning.

Digital hermeneutics

Examining historical material adds its particularities to a study. Current digital historical research has used the concept of ‘digital hermeneutics’ to call for epistemological data aka source criticism and method criticism (Fickers et al., 2022 ; Oberbichler et al., 2022 ; Salmi, 2020 ; Paju et al., 2020 ). It is crucial to understand how the data was formed and by whom, and what kinds of activities and worldviews it reflects. Firstly, the temporal meaning change of the formally similar units has to be taken into account. For example, showing a horse in a newsreel in 1910 and 1990 most likely creates very different interpretations. Secondly, digitised data are no longer in their original format (Fickers, 2021 ), and may contain traces left by the production, storage, archiving, digitising, and acquisition processes. For instance, textual descriptions of newsreel content are often added during the digitisation of the material and thus might reflect the perceptions or diligence of the digitisers rather than the activities of the original newsreel authors (Elo, 2020 ; see also Althaus and Britzman, 2018 ). As our case study shows in Section III, heavily censored data can also offer relevant results, when interpreted with an understanding that it provides the view of the authorities. Gaps in the data can produce meaningful insights. Therefore, it is important to account for which activities and to whom the traces that are being analysed belong. Furthermore, off-the-shelf computational analysis methods are often trained on contemporary materials and may not work similarly well with historical materials without adaptation (Grósz et al., 2022 ; Bhargav et al., 2019 ; Wevers, 2021 ; Wevers and Smits, 2020 ). Finally, the quality of cultural heritage materials can vary greatly, which poses additional challenges when studying long-term developments of audiovisual news.

Towards a unified approach

To summarise, while computational video analysis customarily assumes meaning to be contained in the artefact (i.e. the video), qualitative research and New Cinema History argue that meaning only arises when the artefact comes into contact with its audience and can be perceived as having different meanings. Simultaneously, an analysis that ignores inter-subjective contingency is blind to context; an interpretive framework that ignores inter-objective dependency is blind to structure. Both the content and the context should be taken into account, and, we argue, substantial advances in audiovisual (news) studies can be made by coupling these two positions.

The analysis framework for audiovisual newsreel corpora, as outlined in this paper was co-designed within a research process that started with experimental explorations of newsreel data, while negotiating and integrating methods from a spectrum of disciplines as brought together in the CUDAN ERA Chair project for Cultural Data Analytics at Tallinn University. Oscillating between joint reflections in collaborative group work, including two three-day hackathons, and more concentrated work on individual aspects, eventually led to the proposed generalisation of multidisciplinary collaboration in a systematic research process to make sense of historical newsreels at corpus scale. Following C.P. Snow’s call regarding the necessity to bridge the so-called “two worlds” of scholarly enquiry (Snow, 2001 [1959]), our starting point was that multidisciplinary integration brings forth more than a sum of its components. The specific stages of the proposed framework, explained in more detail below, were discovered by combining the established research processes of cultural data analytics and digital history, while experimenting with different ways of integrating quantitative and qualitative approaches, including expertise that is usually found in computation and the natural sciences

The objective of the framework is to exemplify how qualitative and quantitative approaches can be successfully brought together into a joint research pipeline. Towards this purpose, we combine the strengths of qualitative film history, computational video analysis, computational film studies, and New Cinema History listed in Table 1 , while closing their mutual and common gaps. In sum, we present a framework for systematically studying large collections of historical newsreels covering several decades in the context of their temporal and cultural dynamics, diversity, and functions. We propose bringing together a comprehensive set of aspects for a nuanced understanding of newsreels as an interplay of different modalities and contextual factors. The framework includes both qualitative and quantitative research feeding into a systematic approach and ability to cover large quantities of data. The framework, which we discuss in Section II, constitutes a schematic template for research projects combining quantitative and qualitative approaches (see Fig. 1 ). In Section III, we exemplify the framework using a dataset of “News of the Day” newsreel series produced in the Soviet Union in 1944–1992. Finally, Section IV contains the discussion and concludes the article.

The newsreel framework combines qualitative and quantitative approaches into a research pipeline. It contains ( a ) pairing meaning-making units with variables , ( b ) digital data (source) and method criticism, and ( c ) combining quantitative analysis with qualitative conclusions.

Newsreel Framework

Our framework essentially centres around a workflow pipeline configuration (Oberbichler et al., 2022 ) that includes qualitative and quantitative enquiry (Fig. 1 ). There are three important stages in the pipeline: detecting and pairing the meaning-making units and variables, digital data (source) and methods criticism, plus merging and explaining analysis visualisations of different dimensions of the data (Fig. 1a–c ). The study of newsreels begins with identifying meaningful research questions and data, in relation to preceding research. Perhaps more explicit than in established qualitative approaches, we propose to identify relevant meaning-making units arising from preceding research and qualitative enquiry, and pair them with available variables at the first stage (Fig. 1a ). In the second stage, we account for different temporal layers embedded in digitised heritage data to gain a better understanding of how the variables connect with the meaning-making units and the final conclusions of the study (Fig. 1b ). After this, appropriate analysis methods are selected, keeping in mind the available variables and research questions, followed by computational analysis. In the third stage the selected variables are studied quantitatively, feeding into an examination of the resulting dimensions of analysis to jointly produce final qualitative conclusions (Fig. 1c ). This stage brings the dimensions of analysis together, critically evaluates what the findings jointly report, contextualises them, and responds to the research questions. Adding these three stages to the research pipeline ensures that newsreels are analysed systematically by considering the multidimensional nature of meaning of cultural data (Schich, 2017 ; Cassirer, 1927 ), focusing on variables relevant to the research questions, and accounting for multimodality in the final results. The framework is modular, which means that it allows selecting methods that suit the particular research question or using multiple methods comparatively, while dealing with particular meaning-making units and variables. Qualitative and quantitative enquiry are firmly intermingled and mutually dependent in this research process, as exemplified in our case study below. Importantly, different parts of the research project are continuously adjusted in relation to each other (Schich, 2017 ; Gadamer, 2013 (1960).

While meaning-making units are the elements related to human understanding of what the phenomenon under study is composed of, the variables are the metadata entries or other features of the data that can be directly analysed computationally (cf. the distinction of elements and features in GIS; Zeiler, 1999 ). Detection and pairing of the meaning-making units with the available or traceable variables (Fig. 1a , see also Fig. 2 ) improve critical evaluation of meaning and comparability identified as gaps in preceding research (see Table 1 ). Furthermore, it establishes an explicit connection between the analysed variables and the phenomenon under study, enabling critical evaluation. The preceding literature uses the term ‘cue’ both when referring to what we call here the meaning-making units and variables (e.g. Bordwell, 1991 ; Ren et al., 2018 ), which complicates differentiating between the two. The meaning-making units come from the initial idea of the study, the research question, and the preceding literature, while variables are concretely present in the data. While they arise from different roots, the successful pairing of the two concepts is crucial for a fruitful study.

a Meaning-making units selected from Supplementary Table 1 for further analysis. b Existing and enriched variables of the News of the Day data. Arrows signify data enrichment based on the original data. c Resulting dimensions of analysis that interconnect the meaning-making units and variables.

The meaning-making units are elements that make up the phenomenon under scrutiny. Examples of meaning-making units, as relevant for newsreel research and broadly agreed in literature, include images, voice-over narration, acoustic motifs, the persons, activities, or locations shown, and content topics (Supplementary Table 1 ). Contextual factors are also important, including the socio-political circumstances, other concurrently available mass-communication media, and agency-related issues, like funding and the role of audiences. Relevant meaning-making units can be identified via an extensive literature review of qualitative studies on the topic to see what elements are often suggested and by critically evaluating the gaps. Of course, they may also emerge from analysis itself, in which case the research is firmly going beyond the state of the art.

In addition to the existing feature variables, others can be added, by either manually or algorithmically enriching the data, or adding additional data sources. As Table 2 shows, the most frequent metadata entries in the largest openly available collections of digitised newsreels contain information on production year, newsreel series title, duration, and content annotations either as text or keywords. The metadata entries, together with the available newsreel videos, form the basis for extracting variables. They can be further enriched with information concerning the newsreel authors, distribution, audience reactions, etc. To obtain well-selected units for computational analysis it is crucial to critically evaluate and pair the meaning-making units necessary for responding to research questions with variables that are available or traceable via enrichment. Notably, some variables might reveal meaning-making units indirectly (e.g. the number of people working on newsreels can be indicative of funding and the societal importance of newsreels).

The second stage we propose for the analysis part of the pipeline is to incorporate digital data (source) criticism by taking into account the historical multidimensionality of heritage data, as well as the temporal change affecting the meaning-making units and variables into the study (Fig. 1b ). This stage includes qualitative historical reflection, complementing the two other stages of the framework (Fig. 1 a, c). At this stage, firstly, the researchers scrutinise how the historical traces of the data, coming from production, storage, archiving, or digitising, are present in the data, affecting which variables should be selected for further analysis. The variable can be connected with the different meaning-making units, depending on the point in time and by whom it was created. For example, if a textual description of the contents was created as a newspaper advertisement or censorship card at the time of producing the newsreels (Werenskjold, 2018 ; Althaus and Britzman, 2018 ), the variable connects to the distribution and competition within the cinema market or the political context. If it was created within the digitisation process at a later stage, it should be combined with the interpretations of the later generations of what is noticeable in the contents. Secondly, the researchers will return to this stage after completing computational analysis of the variables to weight the effect of temporal change to the analysis results. As an example, they might reflect upon whether an increasing number of cars detected is due to an explicit choice of the filmmakers, the overall increase of the amount of cars in the society, the fact that the used algorithm detects better new car models than the old ones, or some other reason. Some results may also be absent due to conscious selections in data handling. For example, as our case study in Section III demonstrates, the qualitatively observed absence of footage portraying Stalin before his death in 1953 is most likely a result of de-selection of this material from the data (Fig. 3a ). With the twofold reflections concerning the content and method dependency, this stage addresses the lack of historical contextualisation identified in the preceding literature (see Table 1 ) by proposing to take into consideration the temporal aspects of data both when selecting the variables and when performing the final analysis.

a All News of the Day issues (scatter plot): x-axis publication years, y-axis issue number; the total number of news stories per year based on textual outlines; b number of shots per issue over time; c mean shot length per issue; d shares of news story topics per year classified based on textual descriptions of newsreels using an instructable zero-shot classifier. Each news story is classified with a single class. e A UMAP projection of story embeddings, coloured by the content predictions in ( e ) and ( f ); f annual news story topic distribution averaged over years.

The third stage is that selected variables are computationally examined and visualised as different dimensions of analysis (Fig. 1c ). Evidently, the used research methods should be selected so that they respond to the research questions when applied to the available variables (for method selection and comparison cf. for e.g. Opoku et al., 2016 ; Gentles et al., 2016 ). This stage addresses the lack of multimodality identified in preceding literature (see Table 1 ), and allows to combine newsreel contents with the contexts in a more streamlined manner. These dimensions, focusing, for example, on newsreel production conditions, or visual and content dynamics of newsreels, are further combined thematically or temporally into preliminary findings. Ideally, the dimensions of analysis represent different parts of the newsreel production, content, and distribution process to reach for a more comprehensive understanding of them. The findings are merged with the wider contextual information from the preceding literature.

The approach proposed here arises from discussions within the field of Cultural Data Analytics (Arnold and Tilton, 2023 ; van Noord et al., 2022 ; van Noord, 2022 ; Manovich, 2020 ; Arnold and Tilton, 2019 ; Schich, 2017 ; CUDAN, 2020 –2024). The starting points of this multidisciplinary approach are that cultural phenomena are inherently multi-scale and vary through time and space, that the interactions of particularity and universality are important, and that the meaning of cultural phenomena lies in the multidimensional relations of entities. When reaching for a bigger picture through longitudinal exploration, the main challenge is in maintaining the multitude of the phenomenon under study and simultaneously tracking the dynamics of selected variables. In this circumstance, recognising plurality and multidimensionality is crucial for understanding cultural phenomena, and we should be careful when reducing this multitude into means or homogenous groups (van Noord et al., 2022 ; van Noord, 2022 ; Manovich, 2020 ).

The design of our newsreel framework supports maintaining the multitude of cultural data while tracking its dynamics in a manner that allows comparisons across time and datasets. The following section exemplifies the application of the proposed framework to the analysis of the “News of the Day” newsreel series, published weekly in the Soviet Union from 1944 to 1992.

Materials and Methods

The data used in the case study is a collection of 1747 issues of the Russian-language Soviet newsreel journal News of the Day digitised by Net-Film company covering the years 1944–1992. We scraped the video files of newsreels with metadata containing information on the production year, issue number, authors and brief content descriptions in Russian and English with the permission of the data provider, the Net-Film company. The data is incomplete in many ways: the collection lacks some newsreel issues; the image and audio quality of the videos is low; and the metadata is imperfect. When working with digitised historical data and analysing the results it provides, incompleteness of the data is a common feature that needs to be taken into account (Carrive et al., 2021 ). Simultaneously, as our case study shows below, systematic holes in data can reveal crucial source-critical aspects of the data, informing the whole research. It is part of a historians’ skillset to be able to work with incomplete data, and to decide how far conclusions can be drawn from it (Howell and Prevenier, 2001 ).

The methodology of our case study followed the above proposed phenomenon categorisation by defining the central meaning-making units, and organisation and enrichment of the data to receive corresponding variables. We selected the methods used for analysing the resulting variables based on the team members’ domain expertise and their evaluations on the methods that would best respond to the research question of how the world was depicted in the News of the Day and by what kinds of groups of individuals involved in newsreel production. As the more detailed description of the methods below shows, all the steps of the research process involved intermingled qualitative, quantitative, computational, and human-made processes.

Meaning-making units

The table containing the meaning-making units of newsreels (Supplementary Table 1 ) was prepared by extensive reading of the preceding qualitative literature on newsreels. Identifying meaning-making units in qualitative research was purposeful because qualitative analysis takes a more holistic view to the phenomenon under scrutiny that quantitative approaches. We collected all the meaning-making units mentioned also in passing in the studies. Because scholars use varying terminology, we homogenised and aggregated the labels of the units. In addition to giving a general view, it also helps to pinpoint groups of studies that have different emphases, for example, on more abstract motifs, or those ones emphasising the contextual and agency-related meaning-making units instead of contents.

The matrix of the most frequent variables in the largest openly accessible collections of digitised newsreels (Table 2 ) lists the most commonly used metadata fields and their presence in some of the most well-known digitised newsreel collections. For the purpose of mapping the variety and prevalence of the metadata fields, the matrix lists the metadata entries using a common description, and not the specific entry titles each individual collection uses. Different digitising and archiving projects may use different types of metadata in variable formats, which may necessitate harmonising data in projects using several collections (see also Beals and Bell, 2020 ). In addition to the listed metadata entries, many collections also contain other data. For this mapping, we did not study how well the metadata entries have been filled or the consistency of the data. We have marked with “x” those entries that already exist, and with “i” those entries that can be extracted from the data. When selecting the variables for a study, qualitative evaluation of the historical dimensions of the data is essential.

Data enrichment

We amended the data by explicating further information both from the newsreel videos and metadata. For the videos, we ran shot boundary detection analysis (SBD), extracted the middle frames of each shot, and produced a ResNet50 (He et al., 2015 ) embedding for those frames. From the textual descriptions of newsreel contents in the metadata, we identified places mentioned using Named Entity Recognition (NER), and further geocoded the recognised location by adding lat/long coordinates. We also applied automatic detection of the assumed gender of newsreel directors and other crew members based on the surnames, which are grammatically gendered in Russian (Fig. 2b ). All automated steps involved qualitative and manual validation and correction of the processed results with human expertise in the loop.

News story categories

Each News of the Day issue is split into individual stories (12,707 across the 1747 reels), which have synopsis-like descriptions in the metadata. We also corrected small numbering and consistency issues in a minority of them by hand. We then applied two types of automatic content categorisation to the stories, topic modelling and content classification. Topic modelling (often using Latent Dirichlet Allocation, a form of “soft” clustering) is a common approach in digital humanities and other fields dealing with large text collections. For topics, we use the pretrained model driven approach (Angelov, 2020 , Grootendorst, 2022 ) where texts are first embedded using a word or sentence embedding (we use fasttext; Bojanowski et al., 2017 ) and then clustered, with cluster keywords derived via grouped term-frequency inverse-document-frequency (TF-IDF) scaling. The upside of topic modelling as an explorative approach is that the topics need not be known in advance. The downside is that the clusters may be hard to interpret or even meaningless, and the number of clusters must still be defined in advance. We therefore also experimented with another classification approach.

While in the recent past classifying content or topics would have required purpose-trained supervised classifiers, the advent of instructable large language models (LLMs, such as ChatGPT) makes it possible to predict topic or class prevalence in a “zero-shot” manner. Instead of training or tuning a classifier in a supervised manner on annotated examples, generative LLMs can be simply prompted (instructed) to output relevant text, including topic tags given an input example accompanied with the prompt. The simplest example would be along the lines of “Tag this sentence as being of topic X or Y. Example: [text]”, but we find more verbose prompts with topic definitions yield more accurate results. We defined eight topics of interest based on previous qualitative literature and Soviet history: USSR politics, sports, military (defence, wars), scientific and industrial progress (includes innovation, construction projects, space and aviation), USSR economy and industry, USSR agriculture (excludes other economy topics), natural disasters, social issues and lifestyle (includes education, family, health, leisure, culture, religion topics), and a “misc” topic meant to cover everything else (for the prompts, see the Supplementary material). We tested the zero-shot classification accuracy of two models, OpenAI’s generative pre-trained transformer (GPT) models gpt-3.5-turbo-0301 and gpt-4-0301 (OpenAI, 2023 ). These achieved 88 and 84% accuracy respectively on a hand-annotated 100-story test set. We therefore applied the 3.5 model to the rest of the story synopses, as illustrated in the Results section.

Visual characteristics

We extracted 117 shots on average (ranging from 20 to 247) per newsreel video, with 126 frames (5 s) per shot on average (ranging from 4 to 4508 frames or 0.2 to 180 s). Representing each shot with one frame, the corpus consists of 205.678 frames in total. We used a pre-trained ResNet Convolutional Neural Network (CNN), to embed the extracted video frames in high-dimensional feature space. The original training set for the ResNet50 is ImageNet (Deng et al., 2009 ), a standard collection of contemporary images, and here we apply it to a collection of low-resolution mostly grayscale images. To identify clusters of visually similar frames and detect common themes across reels we projected the embedding space in 2D using common dimension reduction methods such as t-SNE (van der Maaten and Hinton, 2008 ) and UMAP (McInnes et al., 2020 ). Using the Collection Space Navigator (Ohm et al., 2023 ), an interactive open source tool for exploring image collections, was instrumental in exploring the large-scale visual data and gaining new insights to it. We also visualised all the newsreels by sequencing one frame per shot next to one another, effectively in this way creating a storyboard covering all the examined newsreels. In this part we used standard methods with known biases (see, for example Studer et al., 2019 ).

From the results of the Named Entity Recognition (NER) we extracted mentions of cities. We used Wiktionary and authors’ knowledge of Russian grammar to extract additional name-derivative words related to cities. Using this list, we counted mentions of cities in the story descriptions. We qualitatively distinguish five types of city mentions: a) city itself and city dwellers; b) organisations located in the city and named after it; c) names of a region named after the capital (for example ‘Leningrad oblast’) and organisations located there; d) toponyms named after the city which are not located there or in its vicinity including entities, treatises, and historical events (for example ‘Warsaw Pact’); e) not a mention (coincidences and homonyms). We added geo-coordinates taken from Wikipedia to the list of cities to visualise them on a map.

Crew composition

We used newsreel crew metadata to construct a directed graph of co-working relations (Verhoeven et al., 2020 ) where directors and other crew members act as nodes, and edges indicate collaboration on a newsreel issue. The edge direction is drawn from the director to all other crew members and signifies hiring and supervisory relationships. We utilised Levenshtein distance (Levenshtein, 1965 , see also Navarro, 2001 ) to detect potentially misspelt duplicate names and manually checked the need to merge nodes. The crew dataset contains information about 1251 people who worked on 1730 newsreel productions during 1954–1991 across different positions: director (1740 roles by 104 persons), cinematographer (15,145 roles by 1132 persons) and other crew (editors, sounds designers, etc.; 158 roles by 45 persons). Notably, a small portion of staff work across different roles. The dataset results in a network with 1251 unique person nodes and 15,425 person-to-person links. The first nine years of the data collection period were omitted from network analysis due to inconsistent data.

Cinematic and topic trends

The cinematic and topic trends of the News of the Day data show that newsreel production and release as measured by the number of newsreel issues appears to be stable over fifty years (Fig. 3a ) with consistent content shares dedicated to different topics (Fig. 3e ). The first and last few years (1945–1953 and 1990–1992) look somewhat different, but they have much less data than the rest of the period (Fig. 3a ). Newsreel issue numbers recorded, leased, and preserved in the sparse available data before 1954 seem to indicate that newsreels were produced more or less weekly during that period, but only a tiny fragment has been stored and/or digitised (Fig. 3a ). The absence of data before 1954 most likely relates to the ‘de-Stalinization’ of film materials after Stalin’s death in 1953, which included the confiscation of materials with excessive references to the former leader (Heftberger, 2018 ). During 1954–1986, the weekly production was stable, and newsreels were archived, kept, and later digitised systematically (apart from 1965 with missing data). From 1987, the annual number of produced newsreels decreased by half. The 1987 drop in newsreel production volumes coincides with the time of perestroika characterised by economic turbulence and the rethinking of the Soviet media ecosystem (Rodgers, 2014 ).

Topic-wise, the shares of political, economic, agricultural, and social news, classified using the zero-shot prediction approach, remained relatively stable until the mid-1980s when the social, and later political themes began to take more room of the preserved newsreels (Fig. 3f ). The trend shows an annual rhythm (Fig. 3d ), where social news topics usually increased around issue numbers 8–9, which coincided with International Women’s Day, and around issue numbers 48–52 coinciding with the New Year, both officially recognised celebrations in the Soviet Union. Also the topic of agriculture was more prominent around issues 30–40 published in August and September, which were the most important months of harvest.

With a closer look, it is possible to identify subtle changes across the observed period. Although the annual number of issues remained relatively stable during 1954–1986, the number of news stories per issue, determined based on the textual outlines in the metadata, decreased gradually during this time (Fig. 3a ). Also the number of shots in a newsreel decreased over time (Fig. 3b ), while the mean length of shots started to increase towards the end of the period (Fig. 3c ). These results show a contrary trend to the findings of scholars studying Hollywood feature films that indicate shortening shot lengths towards the end of the 20th century (Cutting et al., 2011 ). The reasons for the ‘stagnating’ Soviet newsreel dynamics should be further explored, with candidates obviously including the availability of film material of extended length, and labour cost in post production, such as cutting and composition. While we provide preliminary exploratory results here, quantitative data like these also naturally allow for the testing of specific hypotheses.

Our examination of the central frames of each shot reveals recurring visual patterns that repeat during the whole studied period (Fig. 4 ). Laying out all the frames of every issue into a storyboard shows subtle length and darkness variation of the (digitised) film material, as well as the launch of colour film in the mid-1980s (Fig. 4a right). Placing the frames in the order of year, issue, and scene number allows for comparing the recurring patterns and changes of the newsreel series. For example, the closeup of the storyboard shows that the opening title frames were customarily followed by frames showing a city scene, indicating the place of the news story. This prelude was followed by scenes depicting activities, such as leaders meeting each other (Fig. 4a left). Using the ResNet50 CNN embedding to extract visual features from the central frame of each shot allows us to examine visual similarities across reels. A UMAP projection of the embedded frames reveals aspects of these similarities at least at a coarse-grain level (Fig. 4b ). Consequently the UMAP allows for visual examination, grouping, and annotation of the most prominent image types in the collection, such as “Nature”, “Monumental gatherings”, “People in meetings”, “Closeups of people at work”, ”Industrial production”, “Title frames and other texts”, and “City views”.

a A storyboard of all newsreel issues, x-axis shot number, y-axis publication years and issue numbers in ascending order. The layout of all issues (4a right) shows the temporal variation of issue lengths and the closeup of the storyboard ( a left) visualises the first scenes of issues 6–14 from 1970. b A UMAP projection of ResNet50 embedding of all central frames of each shot with seven most prominent image clusters named by the authors as (1) “Nature”; (2) “Monumental gatherings”; (3) “People in meetings”; (4) “Closeups of people at work”; (5) ”Industrial production”; (6) “Title frames and other texts”; and (7) “City views”. We used the Collection Space Navigator (Ohm et al., 2023 ), i.e. a flexible open-source user interface, for examining the frames and to produce the figure.

City mentions

Our examination of the cities mentioned in the textual descriptions of the newsreel metadata is summarised in Fig. 5 . Spatially, it demonstrates a heavy emphasis on Europe, both within the Soviet Union and globally, while the Asian part of the Soviet Union in East of the Ural Mountains, was far less covered, matching its lower population rates (Fig. 5a, b ). Outside the Soviet Union, the Warsaw Pact socialist countries are the most frequently covered (36% of all mentions despite being 3% of world population in 1970), as well as ‘neutral’ capitalist countries such as Austria and Finland (9% of all mentions despite being less than 0.4% of world population) (Fig. 5 a, b, d). These findings match the consensus among historians studying Soviet history generally (Koivunen, 2016 ; Gilburd, 2013 ; Turoma and Waldstein, 2013 ). Timewise, the number of mentions per year trends downwards (Fig. 5c–e ), which matches the general decrease in the number of stories per year (Fig. 3a ) and is mostly due to the newsreel issues typically having fewer and longer stories in the 1970s and the 1980s than in the earlier period. It is, however, noteworthy that the number of mentions of foreign cities is shrinking even faster (Fig. 5 c, e), emphasising the decline of the fraction of stories dedicated to international events after around 1960. The temporal patterns for some cities demonstrate a variety of interesting qualitative behaviour (Fig. 5e ). Constant popularity of Leningrad/St. Petersburg seems natural in the view of its importance as the second-largest city in the USSR and the “cradle of the revolution”, the upward trend in the mentions of Minsk correlates with the rapid growth of its population in the period under consideration, and the bump in the popularity of Krasnoyarsk in the 1960s coincides with the building of the Krasnoyarsk Hydroelectric Dam, which was a topic of multiple newsreel stories. The decline of the mentions of Odesa require further historical analysis. The data for individual cities is rather sparse and noisy so extracting statistically significant information from it requires application of advanced statistical techniques and will be done in detail elsewhere.

Map showing all the cities mentioned in 1944–1992, ( a ) globally and ( b ) in Europe. The bubble size indicates the number of mentions. c Average number of mentions of top 50 cities per 1000 stories, the red line is the Soviet cities, and the blue line foreign cities. d Heatmap of city mentions per year for the top 50 most-mentioned cities (Moscow excluded due to heavy overrepresentation). e Heatmap of the top-50 most mentioned cities (Moscow excluded) per 1000 stories in the periods of 1954–1964, 1966–1976, and 1977–1992.

The analysis of newsreel production crews reveals production labour market dynamics and labour division between genders over time. Newsreel production crew numbers (Fig. 6a ) closely follow newsreel production volumes (Fig. 3a ), with ten people working on a newsreel on average. Directors who lead the productions are expectedly vastly outnumbered by other crews since newsreels contain multiple stories often shot by different cinematographers (on average nine versus a single director per newsreel). The historical labour market features several prominent directors, who lead multiple teams (as seen from high degree-centrality nodes in the director–crew network and node degree distribution in Fig. 6d–e ), and who pursue long-lasting careers (Fig. 6c ). The analysis of director gender composition reveals the existence of three distinct periods: gender equality during 1945–1959, a women director’s era during 1960–1974, and men director’s era during 1975–1992 (Fig. 6b ).

a Number of individuals working on newsreel production over time, coloured by role. b Number of individuals working as directors over time, coloured by the assumed gender (women and men). c Director career longevity for the top-20 most productive directors. d Newsreel production crew network during 1954–1991, edges drawn from directors to other crew, coloured by role. e Degree distribution for the unipartite directed newsreel production crew network, both axes in logarithm.

Merging and explaining

As we have shown above, each dimension of analysis reveals new avenues for further qualitative and quantitative enquiry. In addition, analysing similar trends, interrelated themes, or temporal sequences overarching different dimensions of analysis, including combining them in statistical modelling, may help to explain the studied phenomenon better. In our case study, interested in the worldviews portrayed in the Soviet newsreels, bringing the results from different dimensions of analysis together points out a period with emerging shifts. The most prominent temporal change, found across all dimensions of analysis, was the time of perestroika , which introduced major political and cultural changes in the Soviet Union (1985–1991). Although some of the identified changes during this period, such as the launch of colour film (Fig. 4a ), likely had little to do with the political changes, the dimensions of analysis show how profoundly the time of change was affecting different spheres of society. The number of yearly newsreel issues was cut in half, and the published issues contained far fewer news stories (1–3 stories per newsreel against the earlier number of 8–10 stories, Fig. 3a ). Simultaneously, the number of filmmakers producing newsreels was rapidly decreasing following the shrinking newsreel production (Fig. 6a, b ). It is possible that the collapsing Soviet economy and decentralising cultural policy together with the prevalence of television overran the outdated media of newsreels in the era characterised by a gradual increase of freedom of speech and press (Rodgers, 2014 ). Digging deeper via qualitative inspection, we can see that in the 1990s the newsreel contents became focused on political meetings held in Moscow, which is visible in the emphasis on political and social topics covered (Fig. 3f ), and in geographical concentration on only a few cities (Fig. 5d ). The newsreels of the perestroika were characterised by long shots of speeches (Fig. 3c ), as many newsreel issues at the time covered extensively the political discussions on the direction of the country, which provided the public in a way first-hand knowledge of who said what in the discussions. Clearly, the worldview that the News of the Day depicted to its audiences, changed in many ways.

While many of these observations are not novel to studies on Soviet history, seeing a signal pointing out the particularity of this period in all the dimensions of analysis is important. It shows that the change of policy in the mid-1980s had way more profound effects than for example, the change of leadership from Khrushchev to Brezhnev in 1964. Quantitative analysis of large amounts of data provides the necessary contextualisation emphasising the specificity of the period, which would not be possible to show in such a concrete manner by a solely qualitative study. The signal evidence furthermore becomes visible to a broader audience, beyond experts whose formation requires years of qualitative research. Additionally, harnessing the findings of the different yet complementary dimensions of analysis together reveals trends that may be interrelated. For example, the diminishing number of crew members can partially explain the decreasing number of issues and shots, and the concentration of the newsreels in only a few cities. With fewer people, it was impossible to cover a larger volume of news material from different places. Focusing only on one dimension of analysis in our case study would not have revealed this possible connection. Finally, all these findings can be enhanced by further qualitative enquiry referencing back to the historical dimensions of the data corpus used in this study and in preceding studies, as well as statistical modelling focusing on any particular questions of interest.

Discussion and conclusions

In this paper, we proposed a framework for studying historical newsreels specifically and audiovisual news more generally in large quantities, while simultaneously maintaining an understanding of the multimodality and complexity of audiovisual data and the relational way of meaning-making associated with them. Analysing newsreels using long-term and large-scale data is beneficial for our understanding of societies in question of the global information landscape, its geographical differences, and the generic features of news content. As our case study on worldviews in the News of the Day newsreel series produced weekly in the Soviet Union during 1944–1992 has demonstrated, combining different dimensions of quantitative analysis together with qualitative enquiry, helps to understand newsreel contents in a long continuum and in a more nuanced way than previously achieved. Quantitative visualisations driven by computational analysis methods help to contextualise smaller-scale qualitative analysis, simultaneously as qualitative analysis allows to explain the detected long-term changes and their nuances. Acknowledging the complexity of the data, i.e. that new quality emerges from large quantities of data, allows for a better-rounded understanding of audiovisual culture. Necessitating a range of co-authors, our approach makes an argument for multidisciplinary research and advocates studying culture by combining different methods and approaches.

The outlined framework is the first attempt to combine the different disciplinary approaches into a comprehensive study of newsreels. Weaknesses in our proposition may of course become apparent when applying it in a variety of studies, yet we argue that this too will necessitate similar multidisciplinary expertise, collaboration, and negotiation. The case study we have presented here provides a brief glimpse into the application of the framework. One limitation of our approach is that while it selects dimensions of analysis intuitively, yet based on expertise of the crowd of co-authors, it does not explore in detail the selection of analysis methods. This will be further explored in the future. In our case study, we have focused on preliminary exploratory enquiry and less on confirmatory analysis or hypothesis testing. Examining the different ways to compare a variety of datasets, coming from different sources, has not been touched upon in this article, and should be further studied to enhance transnational approaches to the study of newsreels. This article has proposed a methodological solution for studying audiovisual news, while the questions of copyright and access to comprehensive collections of audiovisual data and corresponding metadata continue to be major obstacles to further development of this field (Arnold et al., 2021 ). A further potential hurdle in scaling the approach is the necessity of access to high-performance computation infrastructure for the effective processing of large-scale audiovisual data. In sum, however, with this framework, we hope to open a discussion on how to best study audiovisual news in long-term and large-scale data.

Data availability

The data is available at the company’s website ( https://www.net-film.ru/ ). The code used for accessing the data is available at the supplementary materials.

Althaus SL, Britzman K (2018) Researching the issued content of American newsreels. In: Vande Winkel R, Chambers C, Jönsson M (eds.) Researching Newsreels: local, national and transnational case studies. Palgrave Macmillan, Switzerland, p 247–263

Chapter   Google Scholar  

Althaus SL, Usry K, Richards S, Van Thuyle B, Aron I, Huang L, Leetaru K et al. (2018) Global news broadcasting in the pre-television era: a cross-national comparative analysis of World War II Newsreel coverage. J Broadcast Electron Media 62(1):147–167. https://doi.org/10.1080/08838151.2017.1375500

Article   Google Scholar  

Angelov D (2020) Top2Vec: distributed representations of topics, arXiv, https://doi.org/10.48550/arXiv.2008.09470

Arnold T, Scagliola S, Tilton L, and Van Gorp J (2021) Introduction: special issue on audiovisual data in DH. Digit Hum Q 15 (1). http://digitalhumanities.org/dhq/vol/15/1/000541/000541.html

Arnold T, Tilton L (2019) Distant viewing: analyzing large visual corpora. Digit Scholarsh Hum 34:i3–16. https://doi.org/10.1093/llc/fqz013

Arnold T, Tilton L (2023) Distant viewing: computational exploration of digital images. MIT Press, Cambridge, MA. https://doi.org/10.7551/mitpress/14046.001.0001

Bain M, Nagrani A, Schofield D, Berdugo S, Bessa J, Owen J, Hockings KJ, et al. (2021) Automated audiovisual behavior recognition in wild primates. Sci Adv 7(46). https://doi.org/10.1126/sciadv.abi4883

Bakels J-H, Grotkopp M, Scherer T, Stratil J (2020) Matching computational analysis and human experience: performative arts and the digital humanities. Digit Hum Q 14:4

Google Scholar  

Beals M, Bell E (2020) The atlas of digitised newspapers and metadata: reports from oceanic exchanges. https://doi.org/10.6084/m9.figshare.11560059.v1

Bergström Å, Jönsson M (2018) Screening war and peace: newsreel pragmatism in neutral Sweden, September 1939 and May 1945. In: Vande Winkel R, Chambers C, Jönsson M (eds.) Researching newsreels: local, national and transnational case studies. Palgrave Macmillan, Switzerland, p 157–182

Bhargav S, van Noord N, Kamps J (2019) Deep learning as a tool for early cinema analysis. Proceedings of the 1st workshop on structuring and understanding of multimedia heritage contents. SUMAC ’19. Association for Computing Machinery, New York, NY, USA, p 61–68. https://doi.org/10.1145/3347317.3357240

Book   Google Scholar  

Bojanowski P, Grave E, Joulin A, Mikolov T (2017) Enriching word vectors with subword information. Trans Assoc Comput Linguist 5:135–146. https://doi.org/10.1162/tacl_a_00051

Bordwell D (1991) Making meaning: inference and rhetoric in the interpretation of cinema. Harvard University Press, Cambridge

Brasó G, Cetintas O, Leal-Taixé L (2022) Multi-object tracking and segmentation via neural message passing. Int J Comput Vis 130(12):3035–3053. https://doi.org/10.1007/s11263-022-01678-6

Brissman E, Johnander J, Danelljan M, and Felsberg M (2022) Recurrent graph neural networks for video instance segmentation. Int J Comput Vis. https://doi.org/10.1007/s11263-022-01703-8

Broadwell P, Tangherlini TR (2021) Comparative K-Pop choreography analysis through deep-learning pose estimation across a large video corpus. Digit Hum Q 15:1

Burges J, Armoskaite S, Fox T, Mueller D, Romphf J, Sherwood E, Ullrich M (2021) Audiovisualities out of annotation: three case studies in teaching digital annotation with mediate. Digit Hum Q 15:1

Burghardt M, Heftberger A, Pause J, Walkowski N-O, Zeppelzauer M (2020) Film and video analysis in the digital humanities—an interdisciplinary dialog. Digit Hum Q 14:4

Carrive J, Beloued A, Goetschel P, Heiden S, Laurent A, Lisena P, Mazuet F, et al. (2021) Transdisciplinary analysis of a corpus of French newsreels: the ANTRACT project. Digit Hum Q 15 (1). http://digitalhumanities.org/dhq/vol/15/1/000523/000523.html

Cassirer E (1927) Das symbolproblem und seine stellung im system der philosophie. Z für ÄEsthet Allg Kunstwiss 21:295–322

Chambers C (2018) The Irish Question: newsreels and national identity. In: Vande Winkel R, Chambers C, Jönsson M (eds.) Researching newsreels: local, national and transnational case studies. Palgrave Macmillan, Switzerland, p 265–283

Chambers Ciara, Jönsson Mats, Vande Winkel Roel (eds.) (2018) Researching newsreels: local, national and transnational case studies. Palgrave Macmillan, Switzerland

Chapman, J, Glancy M, and Harper S (2007) The new film history: sources, methods, approaches . Springer

Chávez Heras D (2024) Cinema and machine vision: artificial intelligence, aesthetics and spectatorship. Edinburgh University Press, Edinburgh

Clariana-Rodagut A, Hagener M (2023) Transnational networks of avant-garde film in the interwar period. In: Roig-Sanz D, Rotger N (eds.) Global literary studies: key concepts. De Gruyter, Berlin, p 253–277

Cooper A, Nascimento F, Francis D (2021) Exploring film language with a digital analysis tool: the case of Kinolab. Digit Hum Q 15:1

CUDAN Open Lab Seminar series 2020–2024. https://www.youtube.com/@CUDANLab/videos)

Cutting JE, Brunick KL, DeLong JE, Iricinschi C, Candan A (2011) Quicker, faster, darker: changes in Hollywood film over 75 years. I-Percept 2(6):569–576. https://doi.org/10.1068/2Fi0441aap

Dang S-M (2020) Unknowable facts and digital databases: reflections on the women film pioneers project and women in film history. Digit Hum Q 14:4

Deng J, Dong W, Socher R, Li L-J, Li K, Fei-Fei L (2009) ImageNet: a large-scale hierarchical image database. In Proceedings of the IEEE conference on computer vision and pattern recognition , 248–255. https://doi.org/10.1109/CVPR.2009.5206848

Elo K (2020) Big Data, Bad Metadata: a methodological note on the importance of good metadata in the age of digital history. In: Fridlund M, Oiva M, Paju P (eds.) Digital histories. Emergent approaches within the new digital history. Helsinki University Press, Helsinki, pp 103–111 https://doi.org/10.33134/HUP-5-6

Fickers A (2021) Authenticity: historical data integrity and the layered materiality of digital objects. In: Fickers A, Schafer V, Takats S, Zaagsma G (eds.) Digital roots. Historicizing media and communication concepts of the digital age. De Gruyter Oldenbourg, Berlin, pp 299–312 https://doi.org/10.1515/9783110740202-017

Fickers A, Tatarinov J, Heijden T (2022) Digital history and hermeneutics—between theory and practice: an introduction. In: Fickers A, Tatarinov J (eds.) Digital history and hermeneutics: between theory and practice. De Gruyter Oldenbourg, Berlin, pp 1–19 https://doi.org/10.1515/9783110723991

Fielding R (2009) Newsreels. Encyclopedia of journalism, 3 , SAGE Publications, Thousand Oaks, pp 992–994

Gadamer H-G (2013 (1960)) Truth and method . Bloomsbury Academic

Garrett Cooper Mark, Levavy SaraBeth, Melnick Ross, Williams Mark (eds.) (2018) Rediscovering U.S. newsfilm: cinema, television, and the archive. Routledge, London

Gentles SJ, Charles C, Nicholas DB, Ploeg J, McKibbon KA (2016) Reviewing the research methods literature: principles and strategies illustrated by a systematic overview of sampling in qualitative research. Syst Rev 5(1):172. https://doi.org/10.1186/s13643-016-0343-0

Article   PubMed   PubMed Central   Google Scholar  

Gilburd E (2013) The Revival of Soviet Internationalism in the Mid to Late 1950s. In: Gilburd E, Kozlov D (eds.) The Thaw: Soviet Society and Culture during the 1950s and 1960s. University of Toronto Press, Toronto, p 362–401

Grootendorst M (2022) BERTopic: neural topic modeling with a class-based TF-IDF procedure. arXiv https://doi.org/10.48550/arXiv.2203.05794

Grósz T, Kallioniemi N, Kiiskinen H, Laine K, Moisio A, Römpötti T, Virkkunen A, Salmi H, Kurimo M, Laaksonen J (2022) Tracing signs of urbanity in the finnish fiction film of the 1950s: toward a multimodal analysis of audiovisual data. In: Proceedings of the 6th digital humanities in the nordic and Baltic countries conference (DHNB 2022), 3232: 63–78. https://ceur-ws.org/Vol-3232/paper05.pdf

Gulshad S, Long T, van Noord N (2023) Hierarchical explanations for video action recognition. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, p 3703–3708. https://doi.org/10.48550/arXiv.2301.00436

Hanjalic A (2002) Shot-boundary detection: unraveled and resolved? IEEE Trans Circuits Syst Video Technol 12(2):90–105. https://doi.org/10.1109/76.988656

Hasegawa T, Kato S (2019) Dialogue mood estimation from speech sounds clusterized with speakers’ personality traits. In Proceedings of the IEEE 8th global conference on consumer electronics (GCCE) : 399–401. https://doi.org/10.1109/GCCE46687.2019.9015238

He K, Zhang X, Ren S, Sun J (2015) Deep residual learning for image recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), p. 770–778. https://doi.org/10.48550/arXiv.1512.03385

Heftberger A (2018) Digital humanities and film studies. Visualizing Dziga Vertov’s Work. Quantitative methods in the humanities and social sciences. Springer International Publishing, Switzerland, https://doi.org/10.1007/978-3-030-02864-0_4

Hickethier K (2016) The creation of cultural identity through weekly newsreels in Germany in the 1950s: as illustrated by the NEUE DEUTSCHE WOCHENSCHAU and the UFA-WOCHENSCHAU (With a Side Glance at the DEFA Weekly Newsreel DER AUGENZEUGE). In: Imesch K, Schade S, Sieber S (eds.) Constructions of cultural identities in newsreel cinema and television after 1945. Transcript Verlag, Bielefeld, p 39–54. https://doi.org/10.14361/9783839429754-003

Hielscher E (2020) The phenomenon of interwar city symphonies: a combined methodology of digital tools and traditional film analysis methods to study visual motifs and structural patterns of experimental-documentary city films. Digit Hum Q 14:4

Hoffmann K (2018) The commentary makes the difference: an analysis of the Suez War in East and West German Newsreels, 1956. In: Vande Winkel R, Chambers C, Jönsson M (eds.) Researching newsreels: local, national and transnational case studies. Palgrave Macmillan, Switzerland, p 77–92

Howell MC, Prevenier W (2001) From reliable sources: an introduction to historical methods. Cornell University Press, Ithaca

Hu X, Tang C, Chen H, Li X, Li J, Zhang Z (2022) Improving image segmentation with boundary patch refinement. Int J Comput Vis 130(11):2571–2589. https://doi.org/10.1007/s11263-022-01662-0

Imesch Kornelia, Schade Sigrid, Sieber Samuel (eds.) (2016) Constructions of cultural identities in newsreel cinema and television after 1945. Transcript Verlag, Bielefeld, 10.14361/9783839429754

Kandukuri RK, Achterhold J, Moeller M, Stueckler J (2022) Physical representation learning and parameter identification from video using differentiable physics. Int J Comput Vis 130(1):3–16. https://doi.org/10.1007/s11263-021-01493-5

Koivunen P (2016) Friends, ‘potential friends,’ and enemies: reimagining Soviet relations to the First, Second, and Third Worlds at the Moscow 1957 youth festival. In: Babiracki P, Jersild A (eds.) Socialist internationalism in the cold war. Springer International Publishing, New York, pp 219–47 https://doi.org/10.1007/978-3-319-32570-5_9

Kong Y, Fu Y (2022) Human action recognition and prediction: a survey. Int J Comput Vis 130(5):1366–1401. https://doi.org/10.1007/s11263-022-01594-9

Kordopatis-Zilos G, Tzelepis C, Papadopoulos S, Kompatsiaris I, Patras I (2022) DnS: distill-and-select for efficient and accurate video indexing and retrieval. Int J Comput Vis 130(10):2385–2407. https://doi.org/10.1007/s11263-022-01651-3

Lazer DMJ, Baum MA, Benkler Y, Berinsky AJ, Greenhill KM, Menczer F, Metzger MJ, Nyhan B, Pennycook G, Rothschild D (2018) The science of fake news. Science 359(6380):1094–1096

Article   ADS   CAS   PubMed   Google Scholar  

Levenshtein VI (1965) Binary codes capable of correcting spurious insertions and deletions of ones. Probl Inf Transm 1(1):8–17

Liu L, Ouyang W, Wang X, Fieguth P, Chen J, Liu X, Pietikäinen M (2020) Deep learning for generic object detection: a survey. Int J Comput Vis 128(2):261–318. https://doi.org/10.1007/s11263-019-01247-4

van der Maaten L, Hinton G (2008) Visualizing data using T-SNE. J Mach Learn Res 11:9

Maltby R, Biltereyst D, Meers P (eds.) (2011) Explorations in new cinema history: approaches and case studies . Wiley

Manovich L (2020) Cultural analytics. MIT Press, Cambridge, MA

Masson E, Olesen CG, Noord Nvan, Fossati G (2020) Exploring digitised moving image collections: the SEMIA project, visual analysis and the turn to abstraction. Digit Hum Q 14:4

McInnes L, Healy J, Melville J (2020) UMAP: uniform manifold approximation and projection for dimension reduction. ArXiv http://arxiv.org/abs/1802.03426

Morgan M (2008) Reality and media reality. The international encyclopedia of communication , John Wiley & Sons, New Jersey. https://doi.org/10.1002/9781405186407.wbiecr015

Mourchid Y, Renoust B, Roupin O, Văn L, Cherifi H, Hassouni ME (2019) Movienet: a movie multilayer network model using visual and textual semantic cues. Appl Netw Sci 4(1):121. https://doi.org/10.1007/s41109-019-0226-0

Navarro G (2001) A guided tour to approximate string matching. ACM Comput Surv 33(1):31–88. https://doi.org/10.1145/375360.375365

Navitski R, Poppe N (2017) Cosmopolitan film cultures in Latin America, 1896–1960. Indiana University Press, Indiana

Nazir S, Cagali T, Sadrzadeh M, Newell C (2020) Audiovisual, genre, neural and topical textual embeddings for TV programme content representation. In: Proceedings of the IEEE international symposium on multimedia (ISM) : p 197–200. https://doi.org/10.1109/ISM.2020.00041

van Noord N (2022) A survey of computational methods for iconic image analysis. Digit Scholarsh Hum 37(4):1316–1338. https://doi.org/10.1093/llc/fqac003

van Noord N, Olesen CG, Ordelman R, Noordegraaf J (2021) Automatic annotations and enrichments for audiovisual archives. ICAART 1:633–640

van Noord N, Wevers M, Blanke T, Noordegraaf J, and Worring M (2022) An analytics of culture: modeling subjectivity, scalability, contextuality, and temporality. arXiv https://doi.org/10.48550/arXiv.2211.07460

Oberbichler S, Boroş E, Doucet A, Marjanen J, Pfanzelter E, Rautiainen J, Toivonen H, Tolonen M (2022) Integrated interdisciplinary workflows for research on historical newspapers: perspectives from humanities scholars, computer scientists, and librarians. J Assoc Inf Sci Technol 73(2):225–239. https://doi.org/10.1002/asi.24565

Article   PubMed   Google Scholar  

Ohm T, Canet Solá M, Karjus A, and Schich M (2023) Collection space navigator: interactive visualization interface for multidimensional datasets. https://collection-space-navigator.github.io/

Olesen CG, Kisjes I (2018) From text mining to visual classification: rethinking computational new cinema history with Jean Desmet’s digitised business archive. TMG J Media Hist 21(2):127–145. https://doi.org/10.18146/2213-7653.2018.370

Olesen CG, Masson E, Van Gorp J, Fossati G, Noordegraaf J (2016) Data-driven research for film history: exploring the Jean Desmet collection. Mov Image: J Assoc Mov Image Arch 16(1):82–105. https://doi.org/10.5749/movingimage.16.1.0082

van Oort T, Jernudd Å, Lotze K, Pafort-Overduin C, Biltereyst D, Boter J, Dibeltulo S et al. (2020) Mapping film programming across post-war Europe (1952): arts and media. Res Data J Hum Soc Sci 5(2):109–125. https://doi.org/10.1163/24523666-00502009

OpenAI (2023) GPT-4 technical report. arXiv https://doi.org/10.48550/arXiv.2303.08774

Opoku A, Ahmed V, Akotia J (2016) Choosing an appropriate research methodology. In: Ahmed V, Opoku A, Aziz Z (eds.) Research methodology in the built environment: a selection of case studies. Routledge, London, p 32–50

Paju P, Oiva M, Fridlund M (2020) Digital and distant histories: introducing emergent approaches within the new digital history. In: Fridlund M, Oiva M, Paju P (eds.) Digital readings of history. history research in the digital era. Helsinki University Press, Helsinki, p 3–18. https://doi.org/10.33134/HUP-5

Park S, Bellur A, Han DK, Elhilali M (2021) Self-training for sound event detection in audio mixtures. In Proceedings of the ICASSP 2021–2021 IEEE international conference on acoustics, speech and signal processing (ICASSP) : 341–345. https://doi.org/10.1109/ICASSP39728.2021.9414450

Pérez AF, Sanguineti V, Morerio P, Murino V (2020) Audio-visual model distillation using acoustic images. In: Proceedings of the IEEE winter conference on applications of computer vision (WACV) : 2843–2852. https://doi.org/10.1109/WACV45572.2020.9093307

Pozdorovkin M (2012) Khronika: Soviet newsreel at the dawn of the information age . PhD thesis, Harvard University. https://dash.harvard.edu/handle/1/9823973

Pozharliev L, Gallo González D (2018) Martin Luther King’s assassination in Spain’s NO-DOs and in Bulgaria’s Kinopregledi. In: Vande Winkel R, Chambers C, Jönsson M (eds.) Researching newsreels: local, national and transnational case studies. Palgrave Macmillan, Switzerland, p 93–117

Pustu-Iren K, Sittel J, Mauer R, Bulgakowa O, Ewerth R (2020) Automated visual content analysis for film studies: current status and challenges. Digit Hum Q 14:4

Rasheed Z, Shah M (2003) Scene detection in Hollywood movies and TV shows. In: IEEE computer society conference on computer vision and pattern recognition, 2:II–343. https://doi.org/10.1109/CVPR.2003.1211489

Ravessoud C, Haver G (2016) Art exhibitions through newsreels: an avatar for identity politics (1945–1960). In: Imesch K, Schade S, Sieber S (eds.) Constructions of cultural identities in newsreel cinema and television after 1945. Transcript Verlag, Bielefeld, p 101–116. https://doi.org/10.14361/9783839429754-006

Ren H, Renoust B, Viaud M-L, Melançon G, and Satoh S (2018) Generating ‘Visual Clouds’ from multiplex networks for TV news archive query visualization. In: Proceedings of the International Conference on Content-Based Multimedia Indexing (CBMI) : 1–6. https://doi.org/10.1109/CBMI.2018.8516482

Rodgers J (2014) From Perestroika to Putin: journalism in Russia. In: Media Independence , Routledge, London, p 237–256

Roth-Ey K (2011) Moscow prime time: how the Soviet Union built the media empire that lost the cultural cold war. Cornell University Press, Ithaca

Salmi H (2020) What is digital history? Polity, Medford

Salt B (1974) Statistical style analysis of motion pictures. Film Q 28(1):13–22. https://doi.org/10.2307/1211438

Sampaio S (2022) From propaganda to attraction: reassessing the role of the public in the Newsreel Jornal Português (1938–1951). Hist J Film Radio Telev 42(3):470–492. https://doi.org/10.1080/01439685.2021.1976918

Sanguineti V, Morerio P, Del Bue A, Murino V (2022) Unsupervised synthetic acoustic image generation for audio-visual scene understanding. IEEE Trans Image Process 31:7102–7115. https://doi.org/10.1109/TIP.2022.3219228

Article   ADS   PubMed   Google Scholar  

Schich M (2017) The hermeneutic hypercycle. In: Brockman J (ed.) Know this: today’s most interesting and important scientific ideas. Harper Perennial, New York, p 561–563

Schich M (2019) Cultural analysis situs. ART-Dok eprint https://doi.org/10.11588/artdok.00006347

Senocak A, Oh T-H, Kim J, Yang M-H, Kweon IS (2018) Learning to localize sound source in visual scenes. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition : 4358–4366. https://doi.org/10.1109/CVPR.2018.00458

Snow CP (2001) The two cultures. Cambridge University Press, London (1959)

Sommer NM, Velipasalar S, Hirshfield L, Lu Y, Kakillioglu B (2020) Simultaneous and spatiotemporal detection of different levels of activity in multidimensional data. IEEE Access 8:118205–118218. https://doi.org/10.1109/ACCESS.2020.3005633

Studer L, Alberti M, Pondenkandath V, Goktepe P, Kolonko T, Fischer A, Liwicki M, and Ingold R (2019) A comprehensive study of imagenet pre-training for historical document image analysis. In: Proceedings of the international conference on document analysis and recognition (ICDAR) : 720–725. https://doi.org/10.1109/ICDAR.2019.00120

Treveri Gennari D, Sedgwick J (2022) Five Italian cities: comparative analysis of cinema types, film circulation and relative popularity in the mid-1950s. In: Sedgwick J (ed.) Towards a comparative economic history of cinema, 1930–1970. Springer International Publishing, Cham, p 249–279. https://doi.org/10.1007/978-3-031-05770-0_9

Tsivian Y (2009) Cinemetrics, part of the humanities’ cyberinfrastructure. In: Ross M, Grauer M, Freisleben B (eds.) Digital tools in media studies. analysis and research. An overview. Transcript, Bielefeld, p 93–100

Turoma Sanna, Waldstein Maxim (eds.) (2013) Empire de/centered: new spatial histories of Russia and the Soviet Union. Ashgate, Farnham

Tworek HJS (2019) News from Germany: the competition to control world communications, 1900–1945. News from Germany. Harvard University Press, Harvard, https://doi.org/10.4159/9780674240728

Valverde, FR, Valeria Hurtado J, and Valada A (2021) There is more than meets the eye: self-supervised multi-object detection and tracking with sound by distilling multimodal knowledge. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (CVPR) : 11607–11616. https://doi.org/10.1109/CVPR46437.2021.01144

Vande Winkel R, Biltereyst D (2018) Newsreel production, distribution and exhibition in Belgium, 1908-1994. In: Vande Winkel R, Chambers C, Jönsson M (eds.) Researching newsreels: local, national and transnational case studies. Palgrave Macmillan, Switzerland, p 231–246

Veldi M, Bell S, Kuhlmann F (2019) Five-year plan in four: Kolkhoz propaganda in film and documentaries in Estonia. SHS Web Conf 63:10002. https://doi.org/10.1051/shsconf/20196310002

Verhoeven D, Coate B, Zemaityte V (2019) Re-distributing gender in the global film industry: beyond #metoo and #methree. Media Ind J 6(1):135–155. https://doi.org/10.3998/mij.15031809.0006.108

Verhoeven D, Musial K, Palmer S, Taylor S, Abidi S, Zemaityte V, Simpson L (2020) Controlling for openness in the male-dominated collaborative networks of the global film industry. PLOS One 15(6):e0234460. https://doi.org/10.1371/journal.pone.0234460

Article   CAS   PubMed   PubMed Central   Google Scholar  

Wan S, Xu X, Wang T, Gu Z (2021) An intelligent video analysis method for abnormal event detection in intelligent transportation systems. IEEE Trans Intell Transport Syst 22(7):4487–4495. https://doi.org/10.1109/TITS.2020.3017505

Wang D, Zhang S (2022) Unsupervised person re-identification via multi-label classification. Int J Comput Vis 130(12):2924–2939. https://doi.org/10.1007/s11263-022-01680-y

Werenskjold R (2018) Around the world: the first Norwegian newsreel, 1930–1941. In: Vande Winkel R, Chambers C, Jönsson M (eds.) Researching newsreels: local, national and transnational case studies. Palgrave Macmillan, Switzerland, p 51–75

Wevers M (2021) Scene detection in De Boer historical photo collection. In: Proceedings of the 13th international conference on agents and artificial intelligence (ICAART 2021) , 1:601–610. https://doi.org/10.5220/0010288206010610

Wevers M, Smits T (2020) The visual digital turn: using neural networks to study historical images. Digit Scholarsh Hum 35(1):194–207. https://doi.org/10.1093/llc/fqy085

Williams M, Bell J (2021) The Media Ecology Project: Collaborative DH synergies to produce new research in visual culture history. Digit Hum Q 15:1

Winston B (2018) Wofull News from Wales: details at 11. news, newsreels, bulletins and documentaries. In: Vande Winkel R, Chambers C, Jönsson M (eds.) Researching newsreels: local, national and transnational case studies. Palgrave Macmillan, Switzerland, p 15–33

Yang K, Russell B, Salamon J (2020) Telling left from right: learning spatial correspondence of sight and sound. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (CVPR) : 9929–9938. https://doi.org/10.1109/CVPR42600.2020.00995

Ye K, Kovashka A (2022) Weakly-Supervised Action Detection Guided By Audio Narration. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition workshops (CVPRW) : 1527–1537. https://doi.org/10.1109/CVPRW56347.2022.00159

Zeiler M (1999) Modeling our world: the ESRI guide to geodatabase design . ESRI Press

Zhang Q, Chan AB (2022) 3D crowd counting via geometric attention-guided multi-view fusion. Int J Comput Vis 130(12):3123–3139. https://doi.org/10.1007/s11263-022-01685-7

Zhao B, Gong M, Li X (2021) AudioVisual video summarization. IEEE Transactions on Neural Networks and Learning Systems : 1–8. https://doi.org/10.1109/TNNLS.2021.3119969

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Acknowledgements

European Union Horizon2020 research and innovation programme ERA Chair project for Cultural Data Analytics CUDAN (Project no. 810961); National programme of the Ministry of Education and Research of the Republic of Estonia for April 2022–February 2023 (Project no. EKKD77); Estonian Research Council Public Value of Open Cultural Data (Project no. PRG1641); European Union Horizon Europe research and innovation programme CresCine—Increasing the International Competitiveness of the Film Industry in Small European Markets (Project no. 101094988).

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MO, KM, VZ, TO, MT, MM, AK, DCH, MCS, and MS designed research, KM and MO acquired the data, MO, KM, VZ, MT, TO, and HHJ prepared the data, MO, KM, VZ, AK, MT, TO, MM, and MS performed the analysis, and MO, VZ, and MS wrote the manuscript. MO is the first author. MS is the supervising author.

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Oiva, M., Mukhina, K., Zemaityte, V. et al. A framework for the analysis of historical newsreels. Humanit Soc Sci Commun 11 , 530 (2024). https://doi.org/10.1057/s41599-024-02886-w

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Received : 14 July 2023

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DOI : https://doi.org/10.1057/s41599-024-02886-w

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