research paper networking sites

• Research article
• Open access
• Published: 28 March 2022

Social networking sites use and college students’ academic performance: testing for an inverted U-shaped relationship using automated mobile app usage data

• Wondwesen Tafesse   ORCID: orcid.org/0000-0002-1284-7167 1  

International Journal of Educational Technology in Higher Education volume  19 , Article number:  16 ( 2022 ) Cite this article

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With the widespread adoption of social networking sites among college students, discerning the relationship between social networking sites use and college students’ academic performance has become a major research endeavor. However, much of the available research in this area rely on student self-reports and findings are notably inconsistent. Further, available studies typically cast the relationship between social networking sites use and college students’ academic performance in linear terms, ignoring the potential moderating role of the intensity of social networking sites use. In this study, we draw on contrasting arguments in the literature predicting positive and negative effects of social networking sites use on college students’ academic performance to propose an inverted U-shaped relationship. We collected data on social networking sites use by having college students install a tracking app on their smartphones for 1 week and data on academic performance from internal college records. Our findings indicate that social networking sites use indeed exhibits an inverted U-shaped relationship with college students’ academic performance. Specifically, we find that spending up to 88.87 min daily on social networking sites is positively associated with academic performance, but beyond that, social networking sites use is negatively associated with academic performance. We discuss the implications of our findings.

Introduction

With the widespread adoption of social networking sites among college students, discerning the relationship between social networking sites use and college students’ academic performance has become a major research endeavor (Doleck & Lajoie, 2018 ; Koranteng et al., 2019 ; Liu et al., 2017 ; Tafesse, 2020 ). Numerous studies have been published on this topic to date and the relevant literature is accumulating rapidly (Doleck & Lajoie, 2018 ; Masrom et al., 2021 ). However, findings have been highly inconsistent (Astatke et al., 2021 ), with some studies documenting a negative relationship between social networking sites use and academic performance (e.g., Junco, 2015 ; Karpinski et al., 2013 ; Tafesse, 2020 ) and others documenting a positive relationship (e.g., Park et al., 2018 ; Samad et al., 2019 ; Sarwar et al., 2019 ).

Notably, much of the available research relies on student self-reports to measure social networking sites use (Astatke et al., 2021 ; Doleck & Lajoie, 2018 ). Students are asked to self-report the frequency or duration of their social networking sites use. Because students have been shown to substantially underestimate their social networking sites use, however, self-report data is prone to measurement error, thereby potentially biasing the magnitude and direction of reported findings (Felisoni & Godoi, 2018 ; Giunchiglia et al., 2018 ; Wang et al., 2015 ). To overcome these limitations, researchers have begun to employ software programs and mobile applications that can automatically track the frequency and duration of social networking sites use, which enables precise measurement (e.g., Felisoni & Godoi, 2018 ; Giunchiglia et al., 2018 ; Wang et al., 2015 ). Coupled with the use of institutional records to measure students’ academic performance, these latter studies have managed to overcome the measurement difficulties afflicting self-reported data. However, even these more recent efforts typically cast the relationship between social networking sites use and academic performance in linear terms. That is, social networking sites use is proposed to linearly co-vary with academic performance.

In the current study, we maintain that the linear relationship typically tested in the literature may not fully capture the complex interplay between social networking sites use and academic performance. We contend that the relationship between social networking sites use and academic performance can be characterized as an inverted U-shape. The fact that both positive and negative effects have been reported in the literature (Astatke et al., 2021 ; Masrom et al., 2021 ; Raza et al., 2020 ) points to the possibility that social networking sites use might produce both positive and negative academic outcomes depending on the intensity of their use. For instance, heavy use of social networking sites can be detrimental to academic performance by having college students reallocate time away from academic work or requiring them to multi-task (Alt, 2015 ; Junco, 2015 ; Kapriniski et al., 2013 ; Marker et al., 2018 ). Modest use of social networking sites, on the other hand, might contribute positively to academic performance by facilitating collaborative learning and offering informational and entertainment values (Al-Qaysi et al., 2021 ; Hoi, 2021 ; Lampe et al., 2015 ; Lemay et al., 2020 ; Raza et al., 2020 ). Prior studies have suggested that not all social networking sites use is maladaptive (Lemay et al., 2020 ).

We combine the positive and negative effects of social networking sites use reported in the literature into an inverted U-shaped relationship by positing the intensity of social networking sites use as a moderating variable. The inverted U-shaped model fits the data better than the linear model, highlighting the crucial role that the intensity of social networking sites use plays in shaping the relationship between social networking sites use and college students’ academic performance. By demonstrating that social networking sites can be associated with both negative and positive academic outcomes depending on their intensity of use, our approach serves to reconcile empirical inconsistencies observed in the literature (Astatke et al., 2021 ). Further, the findings serve to synthesize the contrasting theoretical perspectives offered in the literature––some arguing for a positive effect of social networking sites use, others arguing for a negative effect––into a coherent curvilinear relationship. Overall, our findings contribute to a more nuanced understanding of the relationship between social networking sites use and college students’ academic performance.

Literature review

Social networking sites: an overview.

Ellison and Boyd ( 2013 ) defined social networking sites as “a networked communication platform in which participants (1) have uniquely identifiable profiles that consist of user-supplied content, content provided by other users, and/or system-level data; (2) can publicly articulate connections that can be viewed and traversed by others; and (3) can consume, produce, and/or interact with streams of user-generated content provided by their connections on the site” (p. 180). This definition emphasizes three defining features of social networking sites.

First, social networking sites allow users to create uniquely identifiable profiles animated by both user- and system-supplied information. Examples of these user- and system-supplied information that define a user’s profile on social networking sites include biographic details, self-descriptions, photos, interests and activities (Ellison & Boyd, 2013 ). These pieces of information facilitate online peer-to-peer networking by revealing users’ identities (Kane et al., 2014 ; Zhang & Leung, 2015 ). Second, social networking sites allow users to articulate connections that can be viewed and traversed by others. These connections are typically manifested in the form of friends lists, followers lists, group memberships, liked pages and so on. These publicly stated connections enable users to discern other users’ social connections, further facilitating peer-to-peer networking activities on the platforms (Ellison & Boyd, 2013 ). Zhang and Leung ( 2015 ) maintained that the ability to traverse and view other users’ connections and activities is an innovative feature of social networking sites that is virtually unknown in traditional forms of communication. Finally, social networking sites allow users to consume, produce and interact with the streams of user-generated content provided by their connections (Kane et al., 2014 ). Users create their content by combining text, images, videos, emoticons, animations and so forth—all languages of social networking sites (Dumpit & Fernandez, 2017 ). As well as sharing their own content, users can consume and interact with other users’ content, by liking, sharing and commenting on them, thereby creating a dynamic and continuous cycle of online interaction and engagement, which is essential to the vitality of social networking sites (Masrom et al., 2021 ; Smith, 2017 ).

College students rely heavily on social networking sites for their daily communication, entertainment and information needs (Ansari & Khan, 2020 ; Doleck et al., 2018 ; Ifinedo, 2016 ; Lemay et al., 2020 ). Studies tracking college students’ social media habits have indicated that students spend a significant amount of time daily, switching between multiple social networking sites such as Facebook, Twitter, Instagram, YouTube and Snapchat (Alhabash & Ma, 2017 ; Dumpit & Fernandez, 2017 ; Felisoni & Godoi, 2018 ; Smith, 2017 ; Wang et al., 2015 ). College students use social networking sites for various purposes including opinion sharing, information acquisition, entertainment, self-documentation, self-expression and social interactions, among others (Alhabash & Ma, 2017 ; Chawinga, 2017 ; Lemay et al., 2020 ). Educational use of social networking sites, such as accessing course information, organizing group work, receiving feedback and interacting with instructors, have also been noted in the literature (Al-Qaysi et al., 2021 ; Al-Rahmi et al., 2020 ; Ansari & Khan, 2020 ; Hoi, 2021 ; Raza et al., 2020 ; Smith, 2017 ).

Review of the empirical literature

The pervasive adoption and use of social networking sites among college students have spurred a flurry of research into how social networking sites use influences academic performance (Masrom et al., 2021 ). Several studies have been published and the relevant literature has accumulated over the past years. In response, several systematic literature reviews (e.g., Astatke et al., 2021 ; Doleck & Lajoie, 2018 ; Masrom et al., 2021 ) and meta-analyses (e.g., Huang, 2018 ; Liu et al., 2017 ) have been carried out. Yet, these reviews and meta-analyses document major inconsistencies in the literature. Despite the expanding literature and efforts to consolidate it, results remain inconsistent. Below, we present a summary of representative works.

In an early study, Karpinski et al. ( 2013 ) looked at the relationship between social networking sites use and academic performance among college students in the USA and Europe. They find that social networking sites use is negatively associated with college students’ academic performance both in the US and European samples, but the association is stronger for the US sample. In another widely cited study, Junco ( 2015 ) investigated the relationship between social networking sites use and college students’ academic performance by considering class standing as a moderating variable. The researcher finds that freshmen suffered the highest decline in academic performance from increased social networking sites use, while seniors were less severely affected. Recently, Tafesse ( 2020 ) finds that increased use of social networking sites is negatively associated with academic performance both directly, and indirectly, via decreased student engagement.

In a study that examined the relationship between social networking sites use and student engagement among Korean college students, Park et al. ( 2018 ) reported a positive relationship. But when used for purposes such as image management and social pressure, social networking sites use tends to reduce student engagement. Similarly, Sarwar et al. ( 2019 ) find that social networking sites use contributes positively to college students’ academic performance both directly, and indirectly, by enabling collaborative learning. Finally, Al-Rahmi et al. ( 2020 ) find that college students’ increased perceptions of social presence, interest, perceived enjoyment and perceived usefulness of social networking sites are positively associated with collaborative learning.

Despite their contributions to a deeper understanding of how social networking sites use influence academic performance, the reviewed studies relied on student self-reports to measure both social networking sites use and academic performance, which might introduce measurement errors by, for instance, eliciting socially desirable answers or artificially inflating the correlation among measured variables due to common method bias (Podsakoff et al., 2003 ). To overcome these measurement issues, researchers have begun to deploy software programs and mobile applications that are installed on students’ PCs or smartphones to automatically track the frequency and duration of social networking sites use (Felisoni & Godoi, 2018 ; Giunchiglia et al., 2018 ; Wang et al., 2015 ). Increasingly also, researchers are obtaining data about students’ academic performance from institutional records instead of student self-reports. Collecting data from multiple sources is one of the most effective procedural remedies against common method bias (Podsakoff et al., 2003 ).

Pertinent among this latter group of studies is a pioneering investigation by Wang et al. ( 2015 ), which tracked the social media behavior of college students in the USA for one week by having them install a software program on their PCs and smartphones. The researchers subsequently divided their sample into heavy versus light users and compared their perceptions of how social networking sites use affect academic performance. Their findings suggest that heavy users felt more distracted and fell behind on schoolwork relative to light users. Although the researchers did not formally test the moderating effect of the intensity of social networking sites use, their findings reveal sharp differences in perceptions between heavy and light users.

In a more recent study, Giunchiglia et al. ( 2018 ) measured social networking sites use by having college students install a mobile usage tracking app on their devices and run it for a week. In addition, they employed time diaries to measure social networking sites use during lecture hours and study time. Their findings indicate that increased social networking sites use during lecture hours and study time is negatively predictive of semester GPA. Conversely, social networking sites inactivity during lecture hours and study time is positively predictive of semester GPA. In another study, Felisoni and Godoi ( 2018 ) tracked college students’ overall smartphone use for one week using a tracking app. They find a negative relationship between increased smartphone use and semester GPA.

Following the latter group of studies, we measured social networking sites use by having college students install a mobile usage tracking app on their smartphones and run it for one week and students’ academic performance using semester and cumulative GPAs obtained from internal college records. However, we departed from previous studies by testing for an inverted U-shaped relationship. Extant studies typically model the relationship between social networking sites use and academic performance linearly, which ignores the potential moderating role of the intensity of social networking sites use. By testing for an inverted U-shaped relationship, we demonstrate the moderating role of the intensity of social networking sites use in the relationship between social networking sites use and college students’ academic performance.

Theoretical perspectives

Two main theoretical perspectives are put forth in the literature to explain the relationship between social networking sites use and college students' academic performance: the time-displacement/multitasking argument; and the collaborative learning argument.

The first perspective holds that social networking sites distract students from attaining deeper engagement with their academic study (Alt, 2015 ; Astatke et al., 2021 ; Cao et al., 2018 ; Doleck et al., 2018 ; Junco, 2012 ; Karpinski et al., 2013 ). Two important theoretical mechanisms are proposed to explain this negative relationship: time displacement and multitasking. The time displacement explanation is based on the notion that time is inelastic and daily human activities are scheduled around a fixed, 24-h cycle. The introduction of a new activity, therefore, comes at the expense of other established activities as less time would be available for them (Nie, 2001 ; Tokunaga, 2016 ). According to the time displacement argument, time spent on social networking sites is time reallocated from important academic activities such as studying, attending classes or doing assignments (Doleck et al., 2018 ; Tafesse, 2020 ). By forcing the reallocation of time from academically productive to academically nonproductive tasks, social networking sites use is argued to adversely affect students’ academic performance (Alt, 2015 ; Cao et al., 2018 ; Tafesse, 2020 ).

The multitasking explanation, on the other hand, suggests that attending to two or more tasks at the same time can result in cognitive overload, which reduces students’ ability to correctly and completely execute the tasks at hand (Junco, 2012 ; Junco & Cotton, 2012 ; Karpinski et al., 2013 ; Lau, 2017 ). The multitasking argument implies that trying to accomplish academic tasks while staying on social networking sites reduces students’ attention span and their cognitive ability to effectively engage in academic work, thereby adversely affecting their academic performance (Junco, 2012 ; Karpinski et al., 2013 ; Lau, 2017 ; Lepp et al., 2015 ).

The second perspective holds that social networking sites can be harnessed to facilitate collaborative learning and motivate students into a more constructive learning engagement (Eid & Al-Jabri, 2016 ; Hoi, 2021 ; Lampe et al., 2015 ; Liu et al., 2017 ; Raza et al., 2020 ). Researchers subscribing to this perspective point to the fact that the interactive and social features of social networking sites can be utilized to exchange information, arrange group work, receive feedback and facilitate interaction with instructors (Al-Rahmi et al., 2020 ; Ansari & Khan, 2020 ; Chawinga, 2017 ; Lampe et al., 2015 ; Smith, 2017 ). Social networking sites emphasize collaboration and group engagement as opposed to individual learning, thereby allowing students to become active partners and socially engaged in the process of exchanging information, discovering knowledge and solving problems, which should increase their overall learning and academic performance (Ansari & Khan, 2020 ; Astatke et al., 2021 ; Lampe et al., 2015 ; Sarwar et al., 2019 ; Smith, 2017 ).

With the growing role of social networking sites as a platform for opinion sharing and information exchange at a societal level (Ellison & Boyd, 2013 ), exposure to social networking sites can further widen students’ perspectives and introduce them to diverse worldviews (Alloway et al., 2013 ; Chawinga, 2017 ; Park et al., 2018 ). Social networking sites could also offer students relief from demanding academic tasks by availing entertaining content, such as funny videos, jokes and memes, which can increase their motivation for subsequent tasks (Ansari & Khan, 2020 ; Eid & Al-Jabri, 2016 ; Phua et al., 2017 ; Raza et al., 2020 ).

We draw on the two contrasting perspectives presented above to propose an inverted U-shaped relationship between social networking sites use and college students’ academic performance. The proposed model anticipates a positive relationship between social networking sites use and academic performance when the intensity of social networking sites use is low and a negative relationship when the intensity of social networking sites use is high.

Methodology

Sampling and data collection.

The current study was carried out at a large public university in an Eastern African country in 2019. The study targeted undergraduate students studying business and economics subjects. Business and economics students were chosen for the simple reason that the researchers involved in the study were affiliated with the Business and Economics College. The necessary ethical clearance was obtained from the Office of the Vice-Dean to conduct the study.

Data on students’ social networking sites use was collected by asking voluntary students to install “App Usage”—a freely available mobile usage tracking app—on their smartphones in the Spring 2019 semester. Although we evaluated several candidate mobile usage tracking apps for the purpose of our study, we settled on App Usage for two reasons. First, App Usage offers an accurate measurement of users’ smartphone activities. We installed App Usage on our smartphones, personally checked its accuracy and we were satisfied with the result. Second, App Usage has an intuitive and convenient feature for downloading and sharing one’s app usage history either via email or messaging apps. Because usage history is rendered in a CSV file format, it facilitates faster data capture and processing. An example of custom reports produced by App Usage is presented in the Appendix.

Due to the sensitivity of the data we were after, we resorted to a snowball approach to recruit participants. We start by recruiting an initial batch of students based on personal rapport and solicited their voluntary participation. We then asked this initial batch to recruit additional participants. Through this process, we recruited about 51 voluntary participants. To minimize the effect of social desirability bias, we excluded students attending any one of our classes. Subsequently, we familiarized the participants with the basic functionality of App Usage and asked them to install it on their smartphones. To increase the number of valid responses from the participants, we took several confidence-building steps. First, we limited the applicable usage history to only one week. Second, we excluded weekends since social media use during weekends can be particularly personal relative to weekdays. Likewise, to minimize the potential impact of installing App Usage on students’ smartphone habits, we let the participants run App Usage for three weeks before asking them to submit their usage history in the fourth week. Further, we let students install App Usage after three weeks into the Spring semester. This allowed us to avoid tracking students’ smartphone activities during exam periods, which might underreport their smartphone behavior.

Eventually, 40 students submitted valid app usage data. The remaining 11 students failed to send in their usage data despite our best efforts. Although relatively small, the final sample (N = 40) was representative of the student population in terms of departmental affiliation (accounting = 47%; management = 28%; marketing = 25%), gender-mix (male = 60%; female = 40%) and academic year (second year = 62%; third year = 38%). Notably, first-year students were underrepresented in our data. This is because the initial batch of participants we approached were all second-and third-year students. However, the departmental affiliation and gender proportion in the data map well to the departmental affiliation and gender proportion of the student population. Table 1 summarizes the sample characteristics.

Measurement of variables

The usage history submitted by the students contained details including the names of the mobile apps they used, the amount of time they spent on each mobile app and the start and end dates of the usage history. We constructed two relevant variables from this data. The first was daily average minutes spent on social networking sites, which was used to measure the intensity of students’ social networking sites use (Felisoni & Godoi, 2018 ; Giunchiglia et al., 2018 ). The second variable was daily average minutes spent on smartphone, which was used to measure the amount of time students spent on their smartphones overall. This second variable was used as a control variable.

In order to construct daily average minutes spent on social networking sites, we first had to identify those applications that would qualify as social networking sites. For this purpose, we turned to the definition by Ellison and Boyd ( 2013 ) discussed in “Social networking sites: An overview”. We analyzed the usage history of each student and identified those mobile apps that offer social networking affordances as explicated in Ellison and Boyd’s definition. This process resulted in the identification of about 24 mobile apps, many of them household names around the world and their official variants, such as Facebook (Facebook Lite), Twitter, Instagram, YouTube (YouTube Go), Messenger (Messenger Lite, + Messenger), Telegram (Telegram+ , Telegram X), IMO, WhatsApp, Viber and Google+ . Some of the less-known names we came across include VidMate, Mobogram and Russogram. Our coding scheme is also consistent with previous categorization of social networking sites. For instance, Smith ( 2017 ) identified several social networking sites used in undergraduate learning, many of these sites are included in our coding.

Data on students’ academic performance were collected from the Office of the Vice-Dean, which is responsible for storing students’ academic records at the college level. We gathered semester and cumulative GPAs. Both GPAs were measured on a four-point scale (0.0 to 4.0). We also gathered information about participants’ departmental affiliation, academic year and gender from the same official source. Table 2 reports the descriptive statistics and pairwise correlation of the measured variables.

Analysis strategy

Traditionally, an inverted U-shaped relationship is empirically established by adding a squared term to the predictor variable of interest—in our case, social networking sites use—to a standard linear regression equation, as shown below:

where \({y}_{i}\) is the semester GPA for student i ; \({X}_{i}\) is the daily average minutes spent on social networking sites by student i ; \({x}_{i}^{2}\) is the squared term of daily average minutes spent on social networking sites by student i ; \({Z}_{ij}\) is the \(j^{\prime}s\) control variable for student i including daily average minutes spent on smartphone, gender, academic year and departmental affiliation; \({\beta }_{0}\) , \({\beta }_{1},\) …, \({\beta }_{j}\) are parameters to be estimated; and \({\varepsilon }_{i}\) is a normally distributed error term.

If β 2 from Eq.  1 is negative and statistically significant, an inverted U-shaped relationship can be claimed. However, this traditional approach has come under growing criticism for being simplistic and lacking in rigor (Haans et al., 2016 ; Simonsohn, 2018 ). Lind and Mehlum ( 2010 ) proposed a stricter approach that requires three necessary and sufficient conditions for establishing an inverted U-shaped relationship. The first condition is β 2 from Eq.  1 should be negative and statistically significant. The second condition is the turning point in Eq.  1 should fall within the data range (i.e., between the minimum and maximum values of the dependent variable). The turning point is arrived at by taking the first derivative of Eq.  1 and setting it to zero, which yields −  β 1 /2β 2 . The third and final condition is the slope at the lower half of the data should be positive and statistically significant and the slope at the upper half of the data should be negative and statistically significant. This condition can be tested by dividing the dataset into two parts, typically by using the turning point as a cutoff point, and estimating two separate linear regression equations for each part of the dataset (Simonsohn, 2018 ).

In addition to Lind and Mehlum’s ( 2010 ) three conditions, one also needs to establish that the quadratic regression model fits the data better than the linear model. If adding the squared term to the linear model leads to a significant improvement in model fit, as measured by a statistically significant R 2 change, for instance, the quadratic regression model should be retained (Weisberg, 2005 ). Otherwise, it has to be rejected in favor of the more parsimonious linear regression model. We analyzed the data according to the three conditions outlined above.

We started off our analysis by estimating the linear regression model. To correct for heteroscedasticity, we reported White’s heteroscedastic consistent standard errors (White, 1980 ). The linear regression model was statistically significant ( F  = 5.844; p  < 0.01), attaining R 2  = 0.401 and adjusted R 2  = 0.293. Likewise, the regression coefficient for daily average minutes spent on social networking sites was negative and statistically significant ( β 1  =  − 0.004; p  < 0.01). Table 3 reports the estimation results of the linear regression model.

Second, we estimated the quadratic regression model (Eq.  1 ). As in the linear model, we reported White’s heteroscedastic consistent standard errors. The quadratic regression model was also statistically significant ( F  = 12.75; p  < 0.01). It attained R 2  = 0.609 and adjusted R 2  = 0.524. The F-change from the linear model ( F lin  = 5.844; p  < 0.01) to the quadratic model ( F qdr  = 12.75; p  < 0.01) was statistically significant at p  < 0.01. We, therefore, retained the quadratic regression model as it offered a better fit to the data than the linear model (Weisberg, 2005 ). Table 4 reports the estimation results of the quadratic regression model.

Importantly, the squared term for the daily average minutes spent on social networking sites in the quadratic regression model was negative and statistically significant ( β 2  =  − 0.0000467; p  < 0.01). This result satisfied the first condition of Lind and Mehlum’s ( 2010 ) test, thereby offering initial evidence for an inverted U-shaped relationship between social networking sites use and academic performance.

The turning point (i.e., −  β 1 / − 2 β 2  =  − 0.0083 / − 2 × 0.0000934) occurred at 88.87 min, which is approximately one and half hours of daily average social networking sites use. This turning point lies well within the data range for daily average minutes spent on social networking sites (minimum daily average minutes spent on social networking sites = 5.62 min, maximum daily average minutes spent on social networking sites = 280.5 min), hence satisfying the second condition of Lind and Mehlum’s ( 2010 ) test.

To test the third condition, we grouped the students into two: low users (n = 25) and high users (n = 15). The turning point was used to create the two groups (i.e., students who spent a daily average of 88.87 min or less were categorized into the low user group; students who spent a daily average of 88.87 min or more were categorized into the high user group). Subsequently, we estimated two linear regression equations for each group. The estimation results are summarized in Tables 5 and 6 . The slope for the low user group was positive and statistically significant ( β 1  = 0.005; p  < 0.1), whereas the slope for the high user group was negative and statistically significant ( β 1  =  − 0.0097; p  < 0.01). Because of the limited observation in both the low and high user groups, we find it reasonable to reject the null hypothesis at p  < 0.1. The statistically significant and positive slope for the low user group and the statistically significant and negative slope for the high user group satisfied the third and final condition of Lind and Mehlum’s ( 2010 ) test.

To summarize, we find strong evidence for an inverted U-shaped relationship between college students’ social networking sites use and academic performance. We should further note that we conducted regression diagnostics (e.g., QQ plots, residual plots) for all estimated models and found that the models were well-behaved. Figure  1 visualizes the regression plots for the linear and quadratic regression models.

Regression plots

Robustness check

We implemented a robustness check to examine whether the inverted U-shaped relationship holds under different specifications of the dependent variable. Specifically, we replaced semester GPA with cumulative GPA as the dependent variable. While semester GPA captures academic performance in a single semester, cumulative GPA captures academic performance for several semesters. Therefore, cumulative GPA offers a more stable measure of academic performance. The results from the main model were fully replicated when cumulative GPA was used as the dependent variable. Specifically, the quadratic regression model fit the data better than the linear model ( R 2 lin  = 0.3 vs. R 2 qdr  = 0.39; F lin  = 3.57, p  < 0.01 vs. F qdr  = 5.34, p  < 0.01). The F-change was significant at p  < 0.05. As in the case of semester GPA, the squared term for daily average social networking sites use was negative and statistically significant ( β 2  =  − 1.21; p  < 0.05). Finally, the linear regression coefficient for the low user group was positive and statistically significant ( β 1  = 0.29; p  < 0.1), while it was negative and statistically significant for the high user group ( β 1  =  − 0.62; p  < 0.01). Overall, the results from the semester GPA model were fully replicated when cumulative GPA was employed as the dependent variable, suggesting that the inverted U-shaped relationship remained robust to a different measure of academic performance.

The pervasive adoption of social networking sites among college students has spurred a stream of research into the implications of social networking sites use for college students’ academic performance (Doleck & Lajoie, 2018 ; Koranteng et al., 2019 ; Masrom et al., 2021 ). Reported findings have been highly inconsistent, however, with some studies reporting negative relationships and others reporting positive relationships (Astatke et al., 2021 ; Masrom et al., 2021 ). Against this backdrop, we proposed and found support for an inverted U-shaped relationship. Following recent advances in the literature (Felisoni & Godoi, 2018 ; Giunchiglia et al., 2018 ), we measured social networking sites use with the help of a tracking app installed on students’ smartphones. Further, we measured students’ academic performance using semester and cumulative GPAs obtained from internal college records. By employing a combination of automatically tracked and institutional data, we avoided the measurement error common in self-reported data (Podsakoff et al., 2003 ).

Our main finding reveals that the inverted U-shaped relationship fits the data better than the linear relationship. The turning point on the inverted U-shaped regression curve occurred at 88.87 min, suggesting that spending up to 88.87 min daily on social networking sites (about an hour and a half) is positively associated with students’ academic performance, while spending more than 88.87 min daily on social networking sites is negatively associated with students’ academic performance. This finding was robust to an alternative specification of academic performance.

It thus appears that, when used modestly, social networking sites are positively associated with students’ academic performance. Modest use is less likely to interfere with students’ academic performance as they will be forced neither to reallocate time away for academic tasks nor to multi-task (Chawinga, 2017 ; Wang et al., 2015 ). In fact, modest use of social networking sites might boost students’ academic engagement (Al-Rahmi et al., 2020 ; Masrom et al., 2021 ). For instance, social networking sites have been shown to facilitate collaborative learning, where students engage in socially interactive learning by completing group work, receiving feedback, sharing course material and interacting with each other and their instructors (Al-Qaysi et al., 2020 ; Eid & Al-Jabri, 2016 ; Hoi et al., 2021 ; Lampe et al., 2015 ). Similarly, social networking sites offer students access to information and entertaining content that might contribute to improved academic performance (Alloway et al., 2013 ; Ansari & Kahn, 2020 ; Lepp et al., 2015 ; Masrom et al., 2021 ; Raza et al., 2020 ). This last point is particularly poignant in the national context of our study, where the media infrastructure is neither well developed nor widely accessible to satisfy college students’ demand for information and entertainment (Tafesse, 2020 ). Social networking sites thus double as a source of information and pastime for the college students in our sample (Alhabash & Ma, 2017 ; Chawinga, 2017 ).

In contrast, heavy use of social networking sites can interfere with students’ academic activities (Koranteng et al., 2019 ; Tafesse, 2020 ). With heavy use, students will be forced either to divert time away from crucial academic tasks or to multi-task, which will eventually hamper their academic performance (Kapriniski et al., 2013 ; Lepp et al., 2015 ). In fact, heavy social networking sites use can degenerate into compulsive behavior, such as excessive use and addiction, which can detriment not only students’ academic performance but also their overall well-being (Alt, 2015 ; Cao et al., 2018 ; Hsiao et al., 2017 ; Masrom et al., 2021 ).

Overall, our work contributes to a more nuanced understanding of the relationship between social networking sites use and academic performance among college students. The inverted U-shaped relationship that we proposed and validated serves to reconcile the empirical inconsistencies observed in the literature in terms of positive and negative effects of social networking sites use (Astatke et al., 2021 ; Masrom et al., 2021 ). As our findings demonstrate, social networking sites can produce both positive and negative academic outcomes depending on the intensity of their use. What is crucial to the relationship is the intensity of use, which can easily be captured by an inverted U-shaped model.

Finally, our study comes with a set of limitations that must be considered while interpreting the findings. First, the study relied on a small set of observations sampled using a snowball approach. As such, the sample may not offer an accurate representation of the total student population. The personal and highly sensitive nature of the data we gathered meant that we had to settle with the small number of participants we were able to recruit. However, the sample size we used is not unusual for studies of this nature. For instance, Felisoni and Godoi’s ( 2018 ) study, which tracked college students’ cellphone use in Brazil, was based on 42 observations. Second, we exclusively studied business and economics students. Since students from other disciplines were not included in our study, the findings may not extend to these other disciplines. Third, our sample is taken from a setting that has its own peculiarities. For instance, students at public universities in our setting live on campus for the entire academic year, have access to free WIFI connection and are connected to the internet almost exclusively by way of their smartphones. The students thus connect to social networking sites—and the internet more generally—at no personal cost to them, which might incentivize heavier use. Moreover, the mainstream media infrastructure in the country is rather underdeveloped, which amplifies the informational and entertainment value of social networking sites for college students. These combinations of factors must be considered when efforts are made to extend the findings to new settings.

With the pervasive adoption and use of social networking sites among college students, probing their relationship with college students’ academic performance has become an important research priority. Building on the extant literature, we proposed and validated an inverted U-shaped relationship between social networking sites use and college students’ academic performance. In so doing, we departed from the more traditional approach that casts the relationship between the two in linear terms.

As our findings suggest, moderate use of social networking sites is positively associated with academic performance, while heavy use is negatively associated with academic performance. These findings highlight the crucial role that the intensity of social networking sites use play in shaping the influence of social networking sites on college students’ academic performance.

To our knowledge, our study is the first to test and find support for an inverted U-shaped relationship between social networking sites use and college students’ academic performance. As such, the proposed model should be validated using fresh data, preferably from new contexts, to develop further confidence in the findings. With further validation, the findings can help in the continued effort to harness social networking sites for productive academic purposes in higher education settings (Masrom et al., 2021 ; Smith, 2017 ).

Availability of data and materials

No data will be publicly available for this study since the data was collected after assuring students that their data will not be publicly shared.

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Acknowledgements

I would like to thank Zeleke Siraye and Elias Shitemam for their support in collecting the data for this study.

Funding Acknowledgement: This research is supported by United Arab Emirate University research grant. (Grant code: G00003359; Funding Number: 31B125).

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Tafesse, W. Social networking sites use and college students’ academic performance: testing for an inverted U-shaped relationship using automated mobile app usage data. Int J Educ Technol High Educ 19 , 16 (2022). https://doi.org/10.1186/s41239-022-00322-0

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The utilization of social networking sites, their perceived benefits and their potential for improving the study habits of nursing students in five countries

• Glenn Ford D. Valdez   ORCID: orcid.org/0000-0002-2799-8216 1 ,
• Arcalyd Rose R. Cayaban 2 ,
• Sadeq Al-Fayyadh 3 ,
• Mehmet Korkmaz 4 ,
• Samira Obeid 5 ,
• Cheryl Lyn A. Sanchez 6 ,
• Muna B. Ajzoon 7 ,
• Howieda Fouly 8 &
• Jonas P. Cruz 9  

BMC Nursing volume  19 , Article number:  52 ( 2020 ) Cite this article

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The abundance of easy and accessible information and the rapid development of social networking sites (SNSs) have proven that the world is small and within reach. The great implication of this interconnectivity is attributable to the change in the learning and sharing environment, which for the most part is something that classrooms are lacking. Considering the potential implications of SNSs in nursing education reveals the benefits of SNSs in allowing students to communicate and interact with a wider audience and beyond the classroom. The aim of this study is to identify the extent of SNS utilization, the perceived benefits of SNSs and the potential of SNSs for improving the study habits of nursing students in five countries (Israel, Iraq, Oman, the Philippines and Turkey).

This study is a quantitative cross-sectional study that determined the relationship between the utilization of SNSs, the perceived benefits of SNSs, and the potential of SNSs for improving the study habits of nursing students in the five participating countries (Israel, Iraq, Oman, the Philippines, and Turkey). This paper is based on carefully analysing the survey responses of a sample of 1137 students from an online hosting site. The online instrument focuses on the extent of the utilization and benefits of SNSs according to their accessibility, usability, efficiency and reliability.

Based on the Pearson correlation coefficient (r) our findings, reveal a significant positive correlation between the extent of a possible improvement in study habits and the extent of SNS utilization in terms of the four domains, namely, accessibility (r = 0.246), usability (r = 0.377), reliability (r = 0.287) and efficiency (r = 0.387).

It can be concluded that there is a significant positive correlation between students’ study habits and the extent of SNS utilization, meaning that the more students devote themselves to their study habits, the higher the level of SNS utilization. The use of SNSs by nursing students has positive and negative implications, and there is greater potential for further improving approaches to nursing education through the adaptation of curricula based on the proper utilization of SNSs.

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In today’s generation, the rapid and ever-changing advances in technology and interconnectivity through networking has dramatically influenced the culture of learning and knowledge acquisition. The abundance of easy and accessible information and the rapid development of social networking sites (SNSs) have proven that the world is small and within reach. The great implication of this interconnectivity is attributable to the change in the learning and sharing environment, which for the most the part is something that classrooms are lacking. Additionally, social media in nursing education have shown great potential for influencing students’ study habits [ 1 ]. Online SNSs (e.g., Facebook, Myspace, Flicker, Twitter, and YouTube) have emerged as the fastest means of exchanging personal and professional information among college students [ 2 ]. SNS utilization is defined as the utilization of information networks as a form of communication widely used for several purposes. SNSs are used to interact with users and to generate content, and in recent years, they have seen expansion with regard to creating and maintaining relationships between people [ 3 ]. The issues related to SNSs are unlimited, but there is growing research on the use of social media as learning tools in higher education [ 4 ]. SNSs function like an online community of web users, depending on the website, and many of online SNSs are based on a shared interest. Once accessed, users may begin to socialize. This socialization may include reading the profile pages of other members and possibly even contacting them. The profiles of SNS users vary according to users’ discretion with regard to privacy and their visibility settings [ 5 ]. In this age of technological acuity, the world has become too small, and communication has become more efficient than ever. SNSs have played a vital role in forging connections, and Facebook is the most popular SNS in use today. Facebook has become one of the most regularly visited websites among college students, and because of its rise in popularity, the subject of SNSs among students and faculty has been a topic of concern. SNSs are seen as an alternative to social interaction, access to information and face-to-face interaction. SNSs, such as Facebook, seem to provide a ready space where the role conflicts that students and faculty often experience in their relationship with university work, staff, academic conventions, and expectations can be worked out in a backstage area. SNSs, such as Twitter, are utilized as a tool for posting explanations in study groups, for academic advising, and for student education [ 5 ]. Many researchers have discussed the broad benefits of SNSs in higher education [ 6 ]. Nursing students have identified three proposed reasons for the use of social media to learn through social networking and to socialize with other students, thus establishing professional social networking [ 7 ]. First, SNSs also allow communication with students through instant messages. Second, they enable rapid responses to questions asked by students, and they facilitate virtual discussions that make students part of a community. Third, SNSs also allow active, interactive and reflective learning [ 8 ]. A study on the use of Facebook for online discussions among distance learners showed that there was more frequent interaction via Facebook compared to the use of a forum, which indicates that Facebook has the potential to be used in online academic discussions [ 9 ]. The use of Twitter allowed connections between students, access to external resources, improved learning, and support to access videos, providing opportunities for reflection, flexibility, collaboration, and feedback [ 10 ]. The use of a social networking tool called Ning verifies the feasibility and effectiveness of integrating interprofessional education, which most students showed interest in learning more about, and optimizing patient care [ 11 ]. The use of social networking platforms is a less expensive way to provide interpersonal education, and it creates the possibility of implementing interprofessional education on a large scale and in the long term [ 11 ]. A study identified that most students agree that the use of SNSs, such as Ning, contributed to adding knowledge and increasing their understanding of content [ 12 ]. A study considering the potential implications of SNS for nursing education revealed the benefits of SNSs in allowing students to communicate and interact with a wider audience and beyond the classroom [ 13 ]. One example is the creation of a research group called the mentor and researcher group (MARG), which creates mentors who use Facebook as a communication platform to promote events and serve as a network to discuss issues and concerns among nursing students [ 14 ]. Students realize that Facebook groups can be an innovative method of studying. Facebook has also been described as being useful in promoting learning among peers and teachers [ 15 ]. SNSs are widely used among college students and are beneficial to them because they have the ability to gather students from all over the world to mingle in one virtual world [ 16 ]. This also means that campuses can now begin to blend the subject areas of classes as well as different campuses. A similar study agreed that students spend, on average, 1–2 h a day on SNSs for educational purposes [ 17 ]. In this respect, a study on social networks and learning stated that students listed learning as a top priority when utilizing SNSs [ 18 ]. In contrast, other studies say that Facebook leads to lower grades [ 17 ]. Students have reported concerns that include time management issues, lack of information and communication technology (ICT) skills and limited technical infrastructure in some higher education institutions [ 6 ]. The use of social media has greatly shown an unlimited influence on a student’s general lifestyle. This research was empirically designed to identify the degree of SNS utilization by nursing students, the perceived benefits of SNSs and their potential for improving the study habits of students. This study also seeks to determine the relationship between the utilization of SNSs, their perceived benefits, and their potential for improving the study habits of nursing students in five countries. That is, this study was conducted in five countries: Israel, Iraq, Oman, the Philippines and Turkey. Geographically and demographically, Israel, Iran, Oman and Turkey are homogenous in terms of their settings and cultural background. On the other hand, although it is also part of Asia, the Philippines is more geographically and demographically different in many ways. According to the Internet World Statistics in 2019, the Philippines, Iran and Turkey were among the top 20 counties in the world with regard to the number of Internet users; on the other hand, in Israel and Oman, 3.8 and 2.2% of the population, respectively, are Internet users [ 19 ]. There is a scarcity of research that specifically addresses nursing education and the use of SNSs. Therefore, this study generally aims to shed light on the potential of SNSs for improving the study habits of nursing students in these five countries.

Research questions and hypotheses

This research seeks to answer the following questions: What is the extent to which SNSs are utilized as a means of communication in terms of educational purposes? What social media network is the most helpful for nursing students? What are the perceived benefits of SNSs in terms of accessibility, usability, efficiency and reliability? Is there a significant relationship between the extent of utilization and the perceived benefits of SNSs among nursing students? Does SNS utilization have the potential to improve the study habits of nursing students?

H01: There is no significant relationship between the extent of SNS utilization and the benefits of SNS among nursing students.

HO 2: Using SNSs has no potential to improve the study habits of students.

Study design

This study adopts a quantitative cross-sectional design to determine the relationship between the utilization and perceived benefits of SNSs and their potential for improving the study habits of nursing students in the five participating countries.

Research settings

This study was conducted in five countries. Country selection and participation involved a voluntary system. This study focused on the utilization and perceived benefits of SNSs and their potential for improving the study habits of regular nursing students in the selected colleges and universities of the participating countries. The study participants consisted of first-year to fifth-year Bachelor of Science in Nursing (BSC) students from the five participating countries.

Sample and sampling techniques

The sample of respondents of this study constituted a 1200-student cohort selected from all the universities that met the set of inclusion criteria, and based on the online forms returned, 1400 links were forwarded. This purposive sampling technique was used considering the criteria for the population, and a post hoc sample was computed via proportion analysis using a confidence interval of 0.65 and a confidence level of 0.95 for a sample of 1137 students. The inclusion criteria were as follows : a. being a BSC student; b. being a resident of one of the five participating countries; and c. having access to online SNSs or similar platforms. The exclusion criteria were as follows : a. residing in a country not included in the study; and b. being students of the investigators/collaborators.

Ethical considerations

This study sought approval from Assiut University in Egypt ( IRB 08/08/2017 number 38 ) and ethical clearance in the respective participating countries. This study is a non-experimental study and did not utilize human subjects. It was performed by seeking permission and approval from the respective focal countries collaborating in this research. The three-part survey tool was administered through the use of an online survey, with a written consent section provided to proceed and to seek the respondents’ willingness to participate in the study. Returning the electronically tallied survey form indicated a willingness to participate. The identities of the participants and their personal information were left undisclosed. Blind tallying was used to secure privacy, and codes were used to maintain the anonymity of the participants. All respondents were informed that they could voluntarily withdraw from the study.

Data gathering procedure

The main communication letter with the approval of the IRB was sought from the preidentified colleges and universities in the five participating countries mentioned above. Once approval from the IRBs in each research setting was obtained, the corresponding co-researchers were in charge of the selection of the study participants based on the inclusion and exclusion criteria. Data collection took place between spring 2017 and fall 2018. Through a hosting site, a web-based online tool was forwarded as a link to the study participants for easy access.

Research instrument

The research instrument was subjected to both internal validity and reliability testing. Face validity and content validity were assessed and screened by two experts in the field of nursing research. A post hoc reliability test was performed, and the results of Cronbach’s α yielded a reliability of 0.92 and a margin of error of 0.8. A three-part questionnaire was utilized. Part 1 of the questionnaire sought to determine the demographic profile of the participants in terms of age, gender, the year level, the type of social media site used, and the country of residence. Part 2 of the questionnaire concerned the extent to which SNSs are utilized as a means of communication for educational purposes among nursing students. Finally, part 3 of the questionnaire addressed the perceived benefits of SNSs for nursing students. Both parts 2 and 3 used a four-point Likert scale. When responding to Likert-based questionnaire items, the respondents specified their level of agreement with a statement. They were asked to check the number that best corresponded to their answer regarding the extent of utilization and the perceived benefits of SNSs among nursing students. The highest score was 4, and the lowest score was 1.

Data analysis

The results of this study were analysed and interpreted using the Statistical Package for the Social Sciences (IBM SPSS 24.0). The weighted mean ( Table  1 and Table  2 ) was used to determine the average extent of SNS utilization among nursing students. It was also used to determine the perceived benefits of SNSs among nursing students in terms of the accessibility, usability, efficiency, and reliability of SNSs. After gathering all the completed questionnaires, the mean was computed and gauged according to the following range and qualitative sinterpretations:

Repeated-measures ANOVA was also utilized to identify any significant differences between the two different mean domains, and a post hoc test was performed using Bonferroni’s α [ 20 ]. The Mann-Whitney U test was used to test two or more independent samples that were drawn from the same population where the level of measurement was ordinal [ 21 ]. Pearson’s r is both descriptive and inferential [ 20 ], and it was used to determine the magnitude and direction of a significant relationship between the extent of utilization and the perceived benefits of SNSs among nursing students and to determine the relationship between students’ demographic profile, SNS utilization and the perceived benefits of SNSs and the potential of SNSs to improve the participants’ study habits. The statistical power used for correlations is 1.

The study recruited 1200 participants, based on which a post hoc sample using proportion analysis yielded 1137 students who were taken as the actual sample for this study. The profile distribution of nursing students grouped by country showed that the students from Israel were mostly 26–28 years old, female and first-year students. The nursing students from Iraq were mostly 20–22 years old, female and second-year students. In Oman, most of the nursing students were also 20–22 years old and female, and they were not classified as being first- to fifth-year students. They were irregular students who could be placed in between year levels depending on their nursing major courses, and they could be clustered in a specific year. In the Philippines and Turkey, most of the students were 20–22 years old, female and third-year students. Overall, the majority of the students were 20–22 years old, female and third-year students ( Table  3 ) .

The percentage distribution of the extent to which SNSs were utilized as a means of communication for educational purposes among nursing students in the five countries showed that the majority of nursing students slightly utilized SNSs in terms of their accessibility (61.3%) and moderately utilized them in terms of usability (60.2%). The distribution also showed that most of them moderately utilized SNSs in terms of their efficiency (45.2%) and reliability (46.8%) ( Table  4 ). Figures  1 , 2 , 3 and 4 show the extent of SNS utilization among nursing students grouped according to age, gender, the year level and country. The results also revealed that nursing students had varied responses in terms of their perception of the extent to which SNSs were utilized as a means of communication. At least 2.1% and at most 6.2% of nursing students did not utilize SNSs, and 27.8 to 61.3% of nursing students slightly utilized SNSs. It was also observed that more than one-fourth (30.6%) to 60.2% of the students moderately utilized SNSs. At most 16.8% of students perceived SNSs as being highly utilized. Moreover, on average, nursing students slightly utilized SNSs in terms of accessibility (2.34) and moderately utilized them in terms of usability (2.81), efficiency (2.74) and reliability (2.66). Similarly, nursing students slightly utilized SNSs in terms of accessibility. Regarding the extent of accessibility, the results indicated that nursing students sometimes used an Internet café (2.33), their campus (1.94), malls (2.42), restaurants (2.12), game consoles (2.23), an iPad (1.76) or USB broadband (2.20). They often accessed SNSs in their own houses (2.88) and via mobile phones (2.52) and portable laptops (3.01). In terms of usability, nursing students moderately utilized SNSs. This result means that they often utilized SNSs to receive updates on school activities (3.10), to gain more knowledge about their current lessons (2.97), to share their thoughts and opinions about discussions (2.79) and to carry out advanced studies (2.74). Sometimes, they utilized SNSs for communication purposes related to their studies (2.40). In terms of reliability, the results revealed that they often relied on SNSs to familiarize themselves with their future lessons (2.71), to receive updates on school activities (2.69), to improve their knowledge and skills (2.79), to participate in group research (2.72) and to carry out assignments and projects (2.75). This result means that they moderately utilized SNSs. In terms of efficiency, nursing students often enhanced their abilities to provide nursing care through SNSs (2.82). They often considered that the sources obtained from SNSs were accurate (2.71) and that they learned proper techniques related to nursing skills by using SNSs (2.56) ( Table  5 ). Nursing students were also recognized by their clinical instructors because of the expertise obtained from SNSs (2.39). This result meant that they moderately utilized SNSs.

Line Chart of the Extent of Utilization of the Nursing Students Across All Domains when grouped by Age

Line Chart of the Extent of Utilization of the Nursing Students Across All Domains when grouped by Gender

Line Chart of the Extent of Utilization of the Nursing Students Across All Domains when grouped by Year

Line Chart of the Extent of Utilization of the Nursing Students Across All Domains when grouped by Country

Regarding the question of what SNS nursing students found to be the most helpful, slightly more than one-fourth of nursing students considered Facebook (25.3%), WhatsApp (26%), and Google (25.8%) to be the most helpful social media networks. The results also showed that some students considered Instagram, Snapchat, e-learning, YouTube, Twitter, and others to be the most helpful. Three of the students (0.3%) claimed that they used no social media networks ( Table  6 ). In terms of usability, reliability, accessibility, and efficiency, the results showed that nursing students perceived SNSs as slightly beneficial in terms of accessibility (2.34). They also revealed that SNSs were moderately beneficial in terms of usability, reliability, and efficiency.

With regard to study habits, nursing students often have different study habits in terms of their time management, study focus, and personal perceptions of learning, as well as receiving good grades and carrying out assignments, in addition to the importance of earning exceptional grades. In terms of time management, students allotted enough time (2.85) for studying (2.74), scheduled a fixed time (2.94), and set the best time so that they could study (2.84), reviewing either every day (2.71) or every week (2.51). They also often considered how to focus entirely on studies (2.87) or how to become interested in their studies (2.93), for example, by seeking a quiet place (3.12) or, sometimes, by studying with music or while watching TV (2.41). Moreover, they often considered studying even without exams (2.70) or completing difficult assignments (2.70). They normally enjoyed learning (2.81), and they were always confident that they could receive good grades (3.10). They also frequently attached importance to earning exceptional grades (3), and they ensured that they knew which homework assignments to carry out (3.10) ( Table  7 ) . The results of the extent of SNS utilization in terms of accessibility, usability, and reliability suggested that the younger the age group of the nursing students, the lower their extent of utilization, except for the 23–25 age group. However, the results of the extent of SNS utilization in terms of efficiency contradicted this possible correlation; it suggested that the younger the age of the students was, the lower the extent of SNS utilization in this area, except for the 23–25 age group. The results further showed that there was a significant difference in the extent of SNS utilization in terms of usability (χ2(4) = 16.038, p  = 0.003) and efficiency (χ2(4) = 12.360, p  = 0.015). There was also a significant result in terms of reliability (χ2(4) = 11.012, p  = 0.026). However, pairwise comparison disconfirmed the result of a significant difference. The extent of SNS utilization in all areas was consistently higher in female nursing students, except for accessibility. This suggested a possible relationship where female students tended to have a higher extent of SNS utilization but not in terms of accessibility. The Mann-Whitney U test was performed, revealing that there was a significant difference in the extent of SNS utilization only in terms of accessibility. This result indicated that the extent of nursing students’ SNS utilization in terms of accessibility was significantly higher in male students than in female students. Since the results indicated a non-significant p -value ( p  > 0.05), this also meant that the extent of nursing students’ SNS utilization in terms of usability ( p  = 0.134), reliability ( p  = 0.264) and efficiency ( p  = 0.586) was the same regardless of gender. Regarding accessibility, fifth-year nursing students had the highest SNS utilization in terms of accessibility (Mn rank = 538.86), reliability (Mn rank = 603.22), and efficiency (Mn rank = 631.38). Fourth-year nursing students consistently had the lowest extent of SNS utilization in terms of usability (Mn rank = 471.68), reliability (Mn rank = 448.22), and efficiency (Mn rank = 419.48) but not accessibility (Mn rank = 486.23). It was also observed that there was a fluctuating pattern as the students’ year level increased, which was consistent with the results presented.

From the initial extent of SNS utilization of first-year nursing students, the extent of SNS utilization of second-year students was lower compared to that of first-year students. The extent of SNS utilization was higher in third-year students than in fourth-year students. Additionally, the extent of SNS utilization among fourth-year students was lower than that among fifth-year students. Inferential testing was performed through the Kruskal-Wallis test. The results of the test revealed that there were significant differences in the extent of SNS utilization in terms of accessibility when grouped by the year level (χ2(4) = 19.897, p  = 0.001), reliability (χ2(4) = 21.345, p  < 0.01), and efficiency (χ2(4) = 33.682, p  < 0.01). However, no significant difference in the extent of SNS utilization in terms of usability was found (χ2(4) = 1.187, p  = 0.880). A significant difference was found between the extent of utilization and the perceived benefits of SNSs in terms of accessibility (χ2(4) = 126.981, p  < 0.01), usability (χ2(4) = 40.096, p  < 0.01), reliability (χ2(4) = 51.915, p  < 0.01), and efficiency (χ2(4) = 147.964, p  < 0.01) ( Table  8 ) . It was observed that Oman and the Philippines had the highest mean ranks among all five countries, except for SNS utilization in terms of usability (where Israel obtained the highest mean rank). This result indicated that nursing students in Oman had the highest SNS utilization in terms of accessibility and reliability. The Philippines had the highest SNS utilization in terms of reliability but with a slight difference compared with Oman. Moreover, Turkey obtained the lowest mean rank in all areas, except in terms of accessibility. This result indicated that Turkey had the lowest SNS utilization in terms of usability, reliability, and efficiency. The extent of SNS utilization by nursing students was the highest in terms of usability (2.81), followed by reliability (2.74), efficiency (2.65) and accessibility (2.34) ( Table  9 ) .

Furthermore, the results of repeated-measures ANOVA revealed that there was a significant difference among the domains of SNS utilization. Hence, in an additional test performed using Bonferroni’s post hoc test, accessibility was significantly lower than usability, reliability or efficiency. However, usability was significantly higher than reliability and efficiency, and reliability was significantly higher than efficiency ( Table  10 ) . Pearson’s r revealed a significant positive correlation between the extent of a possible improvement in study habits and the extent of SNS utilization in terms of the four domains, namely, accessibility (r = 0.246), usability (r = 0.377), reliability (r = 0.287) and efficiency (r = 0.387). This result meant that there was a direct relationship between the two variables and further meant that the more the nursing students studied, the higher the extent of their SNS utilization in terms of accessibility, usability, reliability, and efficiency ( Table  11 ) .

The findings of this study identified SNSs and the relationship between their utilization, their perceived benefits and their potential for improving the study habits of nursing students in five different countries. Based on the analysis of the findings of this study, most student respondents were 20–22 years old, female, and in their third year. Our findings are similar to those of a study conducted in Pakistan, where the majority of the nursing respondents were female and within the 21–25 age group [ 22 ]. A relevant finding explained how social media are an important aspect of today’s adolescents, offering efficiency if properly utilized [ 23 ]. A similar study on social networking identified that SNS addiction was higher in male than in female students [ 24 ].

This study revealed that the majority of the nursing students across the five countries were more engaged in websites and SNSs, such as Facebook, WhatsApp and Google. A study conducted in 2009 in Brazil and Singapore showed the wide utilization of Facebook on a regular basis [ 25 ]. These findings were also obtained in earlier studies where Myspace and Facebook were among the most popular sites among students, even though they were not created for educational purposes [ 26 ]. In the results of this study, it was also evident that the use of SNSs was important for establishing communication for educational purposes, and 61.3% of the respondents utilized SNSs for the purpose of relaying information relevant to their studies.

A study has suggested that SNSs are platforms that can be used to improve educational impacts by adapting modifications in the instructional curricula of medical schools [ 2 ]. The aspect of accessibility is an important factor in today’s generation of Internet-savvy students, and the study findings suggest the great importance of accessibility. It was found that students were able to gain access to their social networking profiles through Internet cafés, malls, restaurants and their campus. A study mentioned that access to information was just a click away and that the accessibility of the information on the Internet and SNSs was widely used, which was inherently identified as the main reason why most students were no longer visiting libraries [ 27 ]. Most students prefer SNSs because of their quick and easy access and, in particular, for the purpose of education and learning.

The usability of SNSs in terms of educational purposes is a topic that needs contextualization, as the study findings showed that nursing students in the five countries use SNSs for educational gains by taking advantage of the Internet to acquire knowledge on current lessons, by receiving updates on ongoing school activities, and by carrying out advanced studies. Many educational institutions are still dependent on a traditional learning system, which does not use the full capacity of SNSs as a tool for teaching and learning [ 28 ]. The results of this study contradict those of a study conducted in Oman, where the findings showed that SNSs were mainly used for entertainment purposes and were less used for educational purposes [ 29 ]. SNSs can present various media, such as photos, videos, interactive interfaces and games, which make them highly engaging among students. Moreover, nursing students engage in more interactive skill-based learning sessions. In terms of reliability, nursing students from the five participating countries identified that SNSs were moderately utilized for the purpose of keeping track of school activities and improving knowledge and skills. Regarding efficiency, students scored high in providing correct data and information, enhanced their abilities to provide nursing care, and learned how to perform proper techniques relevant to their nursing skills. It was also noted that some clinical instructors recognized the expertise of students drawn from SNSs, which was supported by a study intervention using SNSs that taught nursing students about ethical and moral behaviours through humanized mannequins in social networks, such as Facebook [ 30 ].

Advanced teaching strategies and the availability of updated and timely learning materials can be advantageous as learning platforms for nursing students. Overall, the nursing students in all five countries were aligned in that they moderately utilized SNSs. In terms of benefits, the students from the five countries said that SNSs were highly beneficial. According to a study, 54.92% of dental students at a university in India suggested that the usage of SNSs was beneficial for their studies and learning needs [ 31 ]. This result is supported by an online survey on social networking as a learning tool that found that the majority of students perceived SNSs as an innovative method of study support that guided learning and enhanced efficacy [ 17 ]. However, the results of this study contradict study results on the effects of online social networking on student performance that suggest that the time that medical students spend on SNSs could negatively influence their academic achievement [ 32 ]. The negative and positive aspects of SNS utilization are a contentious issue that has yet to be resolved because SNSs can be addictive and their improper usage may lead to less positive outcomes. Studying is a skill, and developing study habits is vital for the academic performance of students [ 33 ]. Some studies strongly advocate the use of SNSs as a means of becoming academically successful. For example, one study mentioned that Facebook and SNSs were considered the greatest distractions among college students, subsequently affecting their study habits and grades [ 34 ]. Based on the perspectives of nursing students with regard to their study habits, the study participants from the five countries unanimously identified time management as essential, and a fixed schedule was important when utilizing social networking platforms. This was evidently described by the results of a study showing that SNSs could enhance performance in a simple task environment but made no difference in a complex performance environment [ 35 ]. SNS utilization was also found to be consistently high among female nursing students. It is a known fact that nursing is female dominated [ 36 ]; there are confirmed gender differences that exist with regard to the technologies adopted, and they occur between genders from the age of 16 to 35 [ 37 ]. These findings are firmly contradicted by a study conducted in China showing that Chinese females were clearly less engaged with technology than Chinese males [ 38 ]. On the other hand, women who were found to have higher introversion and extraversion traits turn to the Internet for social services, such as online chats and discussion groups [ 39 ].

In a geographical and cultural context, it can be seen that in countries such as Iran, Israel, Oman and Turkey, the female gender is given less opportunity for public exposure, which results in a higher use of SNSs, which are viewed as a viable medium to socialize and be engaged with others instead of being physically present. A study observed that cultural considerations influenced the interaction platform of choice and the use of SNSs [ 40 ]. Oman and the Philippines were identified as having the highest SNS utilization. In a study of health science students conducted by Sultan Qaboos University, the findings showed that YouTube, Facebook, and Twitter were the most commonly used social media platforms. The findings generally suggest that usage and addiction are similar worldwide [ 41 ]. On the other hand, in the Philippines, the US-based Pew Research Center said that 88% of Filipinos felt that increasing Internet usage was good for education, given that the Philippines is often dubbed the “social media capital” of the world [ 42 ]. In contrast, with regard to SNS utilization, Turkey ranks lowest according to the findings of Kirschner and Karpinski in Turkey, whose study among undergraduate students revealed that students who reported academic problems were more likely to use the Internet for social networking (e.g., Facebook) purposes [ 43 ]. The results of the hypothesis testing yielded a positive relationship between study habits and the extent of SNS utilization among nursing students in the five participating countries. The levels of nursing students’ engagement in SNS utilization can be most beneficial and relevant when they uses SNS for purposes of studying. SNSs are deemed necessary in this generation of learners, wherein a significant amount of information is within grasp and readily available. The utilization of SNSs for educational purposes has both positive and negative implications [ 44 , 45 ].

Limitations

Our study has several limitations. Due to the cross-sectional nature of the study, it was not possible to explain the causal relationship with students’ demographic profile, such as their geographic location and culture, which will require a more extensive research design and strategy. In addition, the researchers acknowledge the lack of attention paid to the role of faculty members in facilitating the utilization of SNSs among nursing students in the selected countries.

The paucity of research and policies related to the integration of SNSs as a learning tool requires attention from both researchers and policymakers. The nursing students from the five participating countries were female dominated, and the extent of SNS utilization was higher among females. This study also identified that the nursing students moderately perceived the utilization and benefits of SNSs, taking into account accessibility, usability, efficiency and reliability. The most commonly utilized social media platforms in Israel, Iraq, Oman, the Philippines, and Turkey were WhatsApp and Facebook. Regarding the correlations with utilization, perceived benefits and study habits showed a positive relationship among the three factors. Similarly, the significant positive correlation between the study habits of students and the extent of SNS utilization means that the more students devote themselves to their study habits, the higher the level of SNS utilization.

Recommendations

This study further suggests that similar studies in the future should focus not only on the aspects of access, usability, efficiency and reliability but also on the inclusion of behavioural aspects. Cultural differences can also be taken into consideration. The homogeneity of the sample can also be addressed by tapping more diverse nursing student populations. Four out of five participating countries (Israel, Iraq. Oman and Turkey, with the Philippines being the exception) are homogenous in terms of culture and geographic settings. A mixed-method approach in future studies is also recommended to contextualize the confounding influence of culture and geographic location. Although there are several studies on SNSs and academic performance, very few studies in nursing academia have been conducted that focus on skills or psychomotor development through virtual platforms that can also be used in the teaching-learning process. The influences of SNSs on nursing students and their great potential for enhancing the study habits of students are an area of opportunity in regard to developing curricula that are not restricted to the four corners of the classroom. SNSs are by far the most current and the most relevant platforms that can further add to the learning success and academic achievement of nursing students. Tailored strategies for enhancing student participation, interaction and real-life learning are just a few of the advantages that can be obtained by tapping the positive contributions of SNSs as a teaching-learning tool in nursing education.

Availability of data and materials

All data generated or analysed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

Social networking site

Bachelor of Science in Nursing

Institutional review board

Mentor and researcher group

Information and communication technology

Statistical Package for the Social Sciences

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Glenn Ford D. Valdez

Sultan Qaboos University, Muscat, Oman

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University of Bagdad, Baghdad, Iraq

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Ondokuz Mayıs Üniversitesi, Samsun, Turkey

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Max Stern Yezreel Valley College, Jezreel Valley, Israel

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School of Nursing, Northern Luzon Adventist College, Pangasinan, the Philippines

Cheryl Lyn A. Sanchez

Oman College of Health Sciences, Salalah, Dhofar, Oman

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Assiut University, Assiut, Egypt

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Shaqra University, Shaqra, Saudi Arabia

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GFDV, ARC, and SAF – conception of the idea, research design, data collection/field work, data management, analysis, report writing, interpretation of the results, and provision of critical reviewing with intellectual input. GFDV, ARC, SAF, MK, SO, CLS, MBA, HF, and JPC – data collection/field work, data management and provision of critical reviewing with intellectual input. The authors have read and approved the manuscript.

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The study sought approval from Assiut University in Egypt (IRB dated 08/08/2017 number 38) and ethical committee clearance from the Oman-Sultan Qaboos University College of Nursing, Iraq-Bagdad University, Israel Max Stern Yezreel Valley College, Turkey-Ondokuz Mayıs Üniversitesi and Northern Luzon Adventist College, the Philippines. A written consent to participate was obtained from the participants. All participants were at least 18 years old.

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Online social networks security and privacy: comprehensive review and analysis

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• Ankit Kumar Jain   ORCID: orcid.org/0000-0002-9482-6991 1 ,
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With fast-growing technology, online social networks (OSNs) have exploded in popularity over the past few years. The pivotal reason behind this phenomenon happens to be the ability of OSNs to provide a platform for users to connect with their family, friends, and colleagues. The information shared in social network and media spreads very fast, almost instantaneously which makes it attractive for attackers to gain information. Secrecy and surety of OSNs need to be inquired from various positions. There are numerous security and privacy issues related to the user’s shared information especially when a user uploads personal content such as photos, videos, and audios. The attacker can maliciously use shared information for illegitimate purposes. The risks are even higher if children are targeted. To address these issues, this paper presents a thorough review of different security and privacy threats and existing solutions that can provide security to social network users. We have also discussed OSN attacks on various OSN web applications by citing some statistics reports. In addition to this, we have discussed numerous defensive approaches to OSN security. Finally, this survey discusses open issues, challenges, and relevant security guidelines to achieve trustworthiness in online social networks.

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Introduction

When the internet became popular in the mid-1990’s it made it possible to share information in ways that were never possible before. But a personal aspect was still lacking in sharing information [ 1 ]. And then in the early 2000s, social networking sites introduce a personal flavor to online information sharing which was embraced by the masses [ 2 ]. Social networking is the practice of expanding one’s contact with other individuals mostly through social media sites like Facebook, Twitter, Instagram, LinkedIn and many more [ 3 ]. It can be used for both personal and business reasons [ 4 ]. It brings people together to talk, share ideas and interests and make new friends. Basically, it helps people from different geographical regions to collaborate [ 5 ]. Social networking platforms have always been found to be easy to use. This is the reason social media sites are growing exponentially in popularity and numbers. Figure  1 shows the basic constituents of social networks and the fields in which it is playing a major role [ 6 ]. As the figure shows, social networking can be used for entertainment, building business opportunities, making a career, improving one’s social skills, and forging relationships with other individuals [ 7 ]. Facebook and Myspace are among the most preferred social networking sites Since a large chunk of the online population utilize social media platform, it has become a significant medium to promote business, awareness campaign.

Constituents of online social networks

Since people consider social media as a personal communication tool, the importance to safeguard their information stored in these social networking sites is often taken for granted. With the passage of time, people are putting more and more information in different forms on social networks which can lead to unprecedented access to people’s and business information. The amount of information stored in social networks is very enticing for adversaries whose aim is to harm someone. They can create havoc worldwide with this huge amount of information in hands. Moreover, social media has become a great medium of advertisement for marketers and if they do not take social media security issues seriously enough, they make themselves vulnerable to a wide variety of threats and put their confidential data at risk. Also, social network can be classified into many types based on their uses. Social networks can be classified into four broad classifications namely, ‘social connections’, ‘multimedia sharing’, ‘professional’ and ‘discussion forums’. This section discusses the types of social networking sites and vulnerabilities and instances of phishing that have occurred on said classifications. Current problems are also stated with an emphasis on malicious content-based phishing attacks. Figure  2 shows different types of social networking sites can broadly be classified into.

Types of social networking sites

In Social connection, People use this network to connect with people and brands online. Although there are other types of social networking sites available online, this type certainly defines social media now. Sites that come under this category are ‘Facebook’, ‘Twitter’, ‘Google + ’, ‘Myspace’. Although there are advantages of using these sites, it has some disadvantages also. These sites are vulnerable to phishing attacks in numerous ways. An intruder can make a portal that looks identical to a Facebook page. And then may lure users into entering into their credentials in different ways. Some of these methods are:

Sending fake messages which states that their Facebook account is about to be disabled in a few days.

The user may be tricked into clicking a link from the personal message sent by his friend stating that someone has uploaded personal pictures of the user in the given link.

Some attackers send a message claiming that the user’s account needs to be updated to use it further. And a link is given to download that update which contains an address of the malicious site.

Also, multimedia sharing networks are used to share pictures, videos, live videos, and other media online. They give an opportunity to users and brands to share their media online. Sites under this category are ‘YouTube’, ‘Flickr’, ‘Instagram’, ‘Snapchat’. Nowadays every social media has an “inbox” feature where anyone can send messages to their friends and chat with them. Recently, YouTube has also released this feature. This gives the attacker a great opportunity to phish his target. He can send a shortened URL in the message which redirects the user to a malicious website [ 8 ]. Since it is not easy to recognize a shortened URL, whether it is legitimate or not, attackers take advantage and obfuscate their malicious content in shortened URLs. Professional social networks are developed to provide career opportunities to their users. It may provide a general forum or may be focused on specific occupations or interest depending on the nature of the website. ‘LinkedIn’, ‘Classroom2.0’, ‘Pinterest’ are some of the examples of professional social networking sites. Since these social networking sites contain all professional information of the user including email id, an attacker can use these details to send a victim a personalized mail. These emails may be like emails claiming prize-money which contains the malicious link. Similarly, in discussion forums, people use these networks to discuss topics and share opinions. These networks are an excellent resource for market research and one of the oldest forms of social network. ‘Reddit’, ‘Quora’ and ‘Digg’ are some examples of popular discussion forums. In these forums, people also share links related to their research so that users can get more information about their topic of research. Some illegitimate users share malicious links to lead astray users to some phishing websites. In this way, phishing can also be done in discussion forums.

The lasting part of our paper is incorporated as follows. We present different statistics for OSN security in  " Statistics of online social network and media " section. Segment 3 particularizes the positive and negative impacts of online social networking. In Segment 4, we depict different threats that affect the user behavior in OSN platform. We describe the reason behind the OSN security issues in-depth in Segment 5. In  " Solutions for various threats " section, we discuss the defensive solutions for various threats. For user awareness in " Security-guidelines for OSNs user " section, we portray certain security rules to protect your system, account, and information. In the following section, i.e. in  " Open research issues and challenges " section, we portray the open research issues and challenges for OSN users. At last, we conclude our work in  " Conclusion " section.

Statistics of online social network and media

Near about 4 billion users exist in the online internet landscape [ 9 ]. Out of the total population on the internet, there are 2.7 billion monthly dynamic clients on Facebook, 330 million active users on Twitter, 320 million active users on Pinterest, as of Dec 30, 2020 [ 10 ]. Figure  3 illustrates the number of users on different social networking platforms [ 11 ]. According to a report from Zephoria, there is a 16 percent increase year over year in monthly active users of Facebook. Seven new profiles are created every second [ 12 ]. Users uploaded a total 350 million pictures per day. On average 510,000 comments are posted in every 60 s on Facebook, 298,000 statuses are updated, and 136,000 photos are uploaded. Since a huge amount of data is uploaded on Facebook, there is a high chance of having security risks. Anyone can post malicious content hidden inside multimedia data or with shortened uniform resource locators (URLs). There are around 83 million fake profiles which can be of illegitimate users or of professionals doing testing and research. Around 1 lakh websites are hacked daily [ 13 ].

Number of users on different social networking platforms

As per the data depicted in Fig.  4 , the use of social networking sites has amplified exponentially such that there is a large amount of data and information available on these sites which has increased risks of information leakage and has opened doors for several cyber-crimes like data interception, privacy spying, copyright infringement, and information fraudulence. Although some Social Networking Sites like Twitter do not allow disclosing private information to users, some experienced attackers can infer confidential information by analyzing user’s posts and the information they share online. The personal information we share online could give cybercriminals enough to get our email and passwords. We have taken cognizance of popularity and narrowed down the list of networks to keep the scope of study feasible. By extension, the chosen social networks employ state-of-the-art defence strategies. Thus, any possible attacks on these networks would employ state-of-the-art techniques. Transitively, the analysis holds relevance for other social networks as well.

Number of users on social media worldwide (year-wise)

Insights in Fig.  5 presents a positioning of the most banned sorts of hacking. It is as indicated by the reaction of adults to a survey in the United States during January 2021. It reports around 44% of the respondents accept that digital secret activities ought to have the most severe punishments.

Most punishable types of hacking in 2021

Figure  6 portrays the most vulnerable way for information breaches worldwide in 2021, sorted by share of identities exposed [ 14 ]. According to the recent report, 91.6 percent of data breaches resulted in impersonation or stolen identities.

Leading cause of data breaches worldwide in 2020

Nowadays geotagged photos are very popular. People tag their geographical locations along with their pictures and share them online. Some applications have this feature of geotagging which automatically tags the current location inside a picture until and unless the user turns it off manually. This can expose one's personal information like where one lives, where one is traveling, and invites thieves who can target one for robbery. When someone updates their status with their whereabouts on a regular basis, it can pose a threat to their life through possible stalking and robbery. According to a report by Heimdal Security, around 6 lakh Facebook accounts are hacked daily [ 15 ]. Individuals who devote more time on social media and are probable to like the posts of their close friends. The hackers take advantage of this trust. Hackers can also use social media to sway elections. The most popular attacks on social media are like-jacking, which occurs when attackers post fake Facebook like buttons to web pages, phishing sites, and spam emails. The statistics in Table 1 entail the percentage of internet users in the United States who have shared their passwords on their online accounts and to their loved ones as of May 2020. It is sorted by age group. The entire survey depicted that 74% of respondents aged more than 65 and above do not share online passwords with family and friends.

With this remarkable expansion in social networking threats and security issues, numerous specialists and security associations have proposed different solutions for alleviating them. Such solutions incorporate PhishAri for phishing detection [ 16 ], spam detection [ 17 ], GARS for cyber grooming detection [ 18 ], clickjacking detection system [ 19 ], framework to detect cyber espionage [ 20 ], SybilTrap to detect Sybil attacks [ 21 ], worm detection system to detect malware [ 22 ]. Users themselves must be alert while posting any media or information on social networking sites. A strong password should be adopted, and it must not be shared with anyone. One should check the URL while visiting a website and must not click any malicious links. These habits could help a user to some extent to be protected against various cyber-attacks on social media. Table 2 presents a collection of the greatest online information breaks via social media worldwide as of November 2020 [ 23 ].

Positive and negative effects of online social networks based on users perspective

Social media has changed the manner in which individuals see the world and collaborate with each other. The near-universal accessibility and minimal effort of long-range informal communication locales, for example, Facebook and Twitter have assisted millions to stay connected with family and friends [ 28 ]. Similar to many technological revolutions, social networks also have a negative side. We describe some of the positive and negative effects of social networking based on the researchers' perceptions described below.

Positive factors of OSN

The various positive factors that influence the user to create and use the environments are maintaining social relationship, marketing the product and platforms, rescue efforts, and finding common group of people to communicate and share the thoughts.

Maintaining social relationships Social networking sites have proven to be convenient in keeping up with the lives of others who matter to us. It helps to nurture friendship and other social relationships [ 29 ].

Marketing platform Professionals can post work experience and build a network of professionally oriented people on sites such as LinkedIn or Plaxo which are career-building social networks [ 30 ]. They help discover better job opportunities. Marketers can influence their audience by posting advertisements on social networking sites [ 31 ].

Rescue efforts Social media sites play a huge role in rescue and recovery efforts during calamities and disasters [ 32 ]. They connect people during such crucial times when the conventional societal structure has broken down. Bulletins are easily managed by social networking sites which can reunite missing family members. The public can be kept informed using utilities extended by essential service providers through online social networking. Real-time local updates on social media help government officials to better understand the circumstances and make more informed decisions.

Finding common groups Social networking sites help people find groups with common interest [ 33 ]. People can share their likes and dislikes, interests and obsessions and thought and views to these groups which contribute to an open society.

Negative factors of OSN

When the general users use the social network platform, he/she face a lot of trouble that identified by various researchers based on security parameter. Like,

Online intimidation: while making friends is easier on social media, predators can also find victims easily [ 34 ]. The anonymity provided by social networks has been a consistent issue for social media users. Earlier someone was bullied only face-to-face [ 35 ]. Nonetheless, now any individual can bully someone online anonymously.

The exploitation of private information: although creating an account on social networking sites is free of charge, they make their money mostly from the advertisements they show on their websites [ 36 ]. The data once gathered is sold to brokers in relationships without the consent of social media users. Moreover, adversaries can also extract confidential information about their targets from these websites using different attack techniques.

Isolation : social media has surely improved the connection between users but conversely it has also averted real-life social interaction [ 37 ]. People find it easier to follow the posted comments of people they know rather than personally visit or call them [ 38 ].

General addiction: by the records we can depict that social media is more addictive than cigarettes and alcohol. People often feel empty and depressed if they do not check their social media account for a full day.

This paper presents a systematic and in-depth study of threats and security issues that are current and are emerging. More precisely, this study encompasses all the conventional threats that affect the majority of the clients in social networks and most of the modern threats that are prevalent nowadays with an emphasis on teenagers and children. The principle objective of this paper is to give knowledge into the social network’s security and protection. It introduces the reader to all the possible dimensions of online social networks and issues related to them. Our analysis throws light on the prevalent open challenges and issues that need to be discussed to enhance the trustworthiness of online social networks.

The remaining paper is systematized as: " Statistics of online social network and media " section describes various threats that are currently prevalent in social media. " Positive and negative effects of online social networks based on users perspective " section provides reasons for social media security issues.  " Various threats on online social network and media " section discusses solutions that are given by various researchers, " Reasons behind online social media security issues " section consists of some security- guidelines suggested for users, some open issues and challenges in online social media is conferred in  " Solutions for various threats " section, finally, Segment 7 presents the conclusion.

Various threats on online social network and media

Being the technology-based society that we are, and with the prevalence of the internet, we have extended our interaction through the electronic world of the internet. Following are the attacks which users have been observing right from the beginning of social networks.

We have divided threats into three categories i.e. conventional threats, modern threats, and targeted threats (as shown in Fig.  7 ). Conventional threats include threats that users have been experiencing from the beginning of the social network. Modern threats are attacks that use advanced techniques to compromise accounts of users and targeted attacks are attacks that are targeted on some particular user which can be committed by any user for varied personal vendettas.

Classification of threats

Conventional threats

Spam attack.

Spam is the term used for unsolicited bulk electronic messages [ 39 ]. Although email is the conventional way to spread spam, social networking platform is more successful in spreading spam [ 40 ]. The communication details of legitimate users can easily be obtained from company websites, blogs, and newsgroup [ 27 ]. It is not difficult to convince the targeted client to read spam messages and trust it to be protected [ 41 ]. Most of the spams are commercial advertisements but they can also be used to collect sensitive information from users or may contain viruses, malware or scams [ 28 ].

Malware attack

Malware is a noxious programming which is explicitly evolved to contaminate or access a computer system, ordinarily without the information of the user [ 42 ]. An intruder can utilize numerous ways to spread malware and contaminate devices and networks [ 43 ]. For instance, malware may get installed by clicking a malicious URL, on the client’s framework or it might divert the client to a phony site which endeavors to acquire private data from the client. An attacker can inject some malicious script in URLs and clicking on that URLs can make that script run on a system that may collect sensitive information from that system [ 44 ]. In social networking platforms, the malware uses Online Social Network’s (OSN) structure to propagate itself such as the number of vertices, number of edges, average shortest path, and longest path.

A phishing attack is a kind of social engineering attack where the aggressor can acquire sensitive and confidential information like username, password and credit card details of a user through fake websites and emails which appears to be real [ 45 ]. An invader can impersonate an authentic user and may use his/her identity to send fake messages to other users via a social networking platform which contains malicious URL [ 46 ]. That URL might readdress a consumer to the phony website where it asks for personal information [ 47 ]. In the case of SNS, an assailant needs to attract the client to a phony page where he can execute a phishing attack. To accomplish this, the assailant uses different social engineering methodologies. For example, he can send a message to a user which says, “your personal pictures are shared on this website, please check!”. By clicking on that URL, the user is redirected to a fake website which looks like some legitimate social networking site.

Identity theft

In this sort of assault, the assailant utilizes someone else’s identity like social security number, mobile, number, and address, without their permission to commit attackers [ 48 ]. With the help of these details, the attacker can easily gain access to a victim's friend list and demand confidential information from them using different social engineering techniques [ 49 ]. Since the attacker impersonates a legitimate user, he can utilize that profile in any conceivable way which could seriously affect authentic clients [ 50 ].

Modern threats

Cross-site scripting attack.

Cross-site scripting is a very prevalent attack vector among infiltrators. The attack is abbreviated as XSS and is also known as “Self-XSS” [ 51 ]. Fundamentally, the attack executes a malicious JavaScript on the victim’s browser through different techniques. These are classified as persistent, reflected, and DOM-based XSS attacks [ 52 ]. The browser can be hijacked with just a single click of a button which may send a malicious script to the server [ 53 ]. This script is boomeranged back to the victim and gets executed on the browser. Attractive links and buttons in popular social media sites like Twitter and Facebook can trick the user into following URLs [ 54 ]. Worse yet, some users may feel compelled to copy and paste JavaScript containing links onto their browser's address bar [ 55 ]. These attacks can either steal information or act as spyware. Such attacks can also hijack computers to launch attacks on unsuspecting users. The real perpetrator of the attack is hidden behind the compromised machine.

Profile cloning attack

In this attack, the assaulter clones the users’ profile about which he has a prior knowledge. The attacker can use this cloned profile either in the same or in a different social networking platform to create a trusting relationship with the real user’s friends [ 56 ]. Once the connection is established, the attacker tricks the victim’s friends to believe in the validity of the fake profile and catch confidential information successfully which is not shared in their public profiles. This attack can also be used to commit other types of cyber-crimes like cyberbullying, cyber-stalking, and blackmailing [ 45 ].

In hijacking, the adversary compromises or takes control of a user’s account to carry out online frauds [ 57 ]. The sites without multifactor authentication and accounts with weak passwords are more vulnerable to hijacking as passwords can be obtained through phishing [ 58 ]. If we do not have multifactor authentication, then we lack a secondary line of defense [ 59 ]. Once an account is hijacked, the hijacker can send messages, share the malicious link, and can change the account information which could harm the reputation of the user [ 60 ].

Inference attack

Inference attack infers a handler’s confidential information which the user may not want to disclose, through other statistics that is put out by the user on some Social Networking Site (SNS) [ 61 ]. It uses data mining procedures on visibly available data like the user’s friend list and network topology [ 62 ]. Using this technique, an attacker can find an organization’s secret information or a user’s geographical and educational information [ 45 ].

Sybil attack

In Sybil attack, a node claims multiple identities in a network [ 63 ]. It can be harmful to social networking platforms as they contain a huge number of users who are coupled through a peer-to-peer network [ 64 ]. Peers are the computer frameworks which are associated with one another by means of the internet and they can share records straightforwardly without the need of a central server [ 32 ]. One online entity can make several fake identities and use those identities to distribute junk information, malware or even affect the reputation and popularity of an organization. For instance, a web survey can be manipulated utilizing various Internet Protocol (IP) delivers to submit an enormous number of votes, and aggressor can outvote a genuine client [ 33 ].

Clickjacking

Clickjacking is a procedure in which the invader deceives a user to click on a page that is different from what he intended to click [ 65 ]. It is also known as User Interface redress attack. The attacker exploits the vulnerability of the browsers to perform this attack [ 66 ]. He loads another page over the page which the user wants to access, as a transparent layer [ 67 ]. The two known variations of clickjacking are likejacking and cursorjacking. The front layer shows the substance with which the client can be baited. At the point when the client taps on that content he actually taps the like button. The more individuals like the post, the more it spreads.

In cursorjacking attacker replaces the actual cursor with a custom cursor image. The actual cursor is shifted from its actual mouse position. In this manner, the intruder can trick a consumer to click on the malicious site with clever positioning of page elements [ 68 ].

De-anonymization attack

In quite a lot of social networking sites like Twitter and Facebook, users can hide or protect their real identity before releasing any data by using an alias or fabricated name [ 69 ]. But if a third party wants to find out the real identity of the user, it can be done by simply linking the information leaked by these social networking sites [ 70 ]. They use strategies such as tracking cookies, network topologies, and user group enrollment to uncover the client’s genuine identity [ 71 ]. It is a sort of information mining method in which mysterious information is cross-referred to other information sources to re-recognize the unknown information [ 60 ]. An attacker can collect information about the group membership of a user by stealing history from their browser and by combining this history with the data collected. Thus the attacker can de-anonymize the user who visits that attacker’s website [ 72 ].

Cyber espionage

Cyber espionage is an act that uses cyber capabilities to gather sensitive information or intellectual property with the intention of communicating it to opposing parties [ 73 ]. These attacks are motivated by greed for monetary benefits and are popularly used as an integral part of military activity or as a demonstration of illegal intimidation [ 74 ]. It might bring about a loss of competitive advantage, materials, information, foundation or death toll. A social engineer can perform social engineering assaults using social networking sites. He can acquire important data like worker’s assignment, email address, and so forth utilizing social networking sites [ 75 ].

Targeted threats

• Cyberbullying

Cyberbullying is the use of electronic media such as emails, chats, phone conversations, and online social networks to bully or harass a person [ 76 ]. Unlike traditional bullying, cyberbullying is a continuous process [ 77 ]. It is continuously maintained through social media [ 78 ]. The attacker repeatedly sends intimidating messages, sexual remarks, posts rumors, and sometimes publishes embarrassing pictures or videos to harass a person [ 79 ]. He can also publish personal or private information about the victim causing embarrassment or humiliation. Cyberbullying can also happen accidentally. It is very difficult to find out the tone of the sender over text messages, instant messages, and emails. But the repeated patterns of such emails, texts, and online posts are rarely accidental [ 80 ].

• Cyber grooming

Cyber grooming is establishing an intimate and emotional relationship with the victim (usually children and adolescents) with the intention of compelling sexual abuse [ 81 ]. The principle point of cyber grooming is to acquire the trust of the youngster and through which intimate and individual information can be attained from the child [ 82 ]. The data is often voluptuous in nature through sexual conversations, pictures, and videos which gives the attacker an advantage to threaten and blackmail the child [ 83 ]. Assailants frequently approach teenagers or kids through counterfeit identity in child-friendly sites, leaving them vulnerable and uninformed of the fact that they have been drawn closer with the end goal of cyber grooming. However, the victim can also unknowingly initiate the grooming process when they get rewarding offers, for example, cash in return for contact details or personal photographs of themselves. In some cases, the victim knows about the fact that he/she is conversing with an adult which can prompt further commitment in sexual activities. However, it is with the individual under the age of consent and in this manner constitutes a crime. The anonymity and accessibility of advanced media permit groomers to move toward various youngsters simultaneously, exponentially increasing the instances of cyber grooming. Despite what might be expected, there are a couple of instances of feelings for the crime of cyber grooming worldwide, as 66% of the world's nations have no particular laws with respect to cyber grooming of children [ 84 ].

Cyberstalking

Cyberstalking is the observing of an individual by the means of internet, email or some other type of electronic correspondence that outcomes in fear of violence and interferes with the mental peace of that individual [ 85 ]. It involves the invasion of a person’s right to privacy. The attacker tracks the personal or confidential information of the victims and uses it to threaten them by continuous and persistent messages throughout the day. This conduct makes the victim exceptionally worried for his own safety and actuates a type of trouble, fear or disturbance in him [ 86 ]. Most of the individuals these days share their personal information like telephone number, place of residence, area, and schedule in their social networking profile. In addition, they likewise share their location-based data. An assailant can gather this data and use it for cyberstalking [ 87 ].

Reasons behind online social media security issues

Social media addresses one of the most unique, unstructured, and unregulated datasets anyplace in the advanced world and this scene is arising quickly all over the globe [ 88 ]. Every day millions of people upload their photos and other multimedia content on social media to share it with their friends. This is prompting the development of digital risk monitoring [ 89 ]. The development of web-based media has presented new security standards that put clients (representatives, clients, and partners) solidly in the aggressor’s line of sight. The social network has become the new digital milestone where attackers think that it's simple to target victims. It has presented one of the biggest, most powerful dangers to authoritative security. Attackers influence social media for the accompanying three reasons (as shown in Fig.  8 ):

The scale of social media: since a huge mass of people spend their time on social media for various purposes, attacks can spread like any other viral trend. The attacker can use hashtags, clickbait, and trending topics to announce their malware which might be focused on everyone or to some particular gathering of individuals. This represents a tremendous challenge for security experts to overcome physically.

Trusted nature of social media: adversaries take advantage of the trusting nature of social media. People sometimes accept an unknown friend request on the basis of mutual friends that requester has. They easily visit the link posted by their friends without thinking much about a possible security breach. Over one-third of the total population on social media acknowledge unknown friend requests, making online media perhaps the best mode for acquiring the trust of a target.

Invisibility to security team: majority of people in the world spend most of their time on social media networks. Observing this enormous populace is extremely troublesome as security teams do not have tools to broaden their perceptibility beyond a specific border into the social media domain where employees are intensively vulnerable to be compromised.

Reasons for social media security issues

Solutions for various threats

Many researchers in both academia and industries are constantly trying to find solutions for the aforementioned threats in social media. They have proposed many solutions and some approaches to combat these threats. This section provides a discussion on various methods and approaches proposed by different researchers on SNS security. We have classified solutions into two groups namely social network operator solutions and academic solutions. Figure  9 shows the classification.

Classification of solutions to threats

Social network operator solutions

Authentication mechanism.

To make sure that only a legitimate user is logging or registering in a social network and not a socialbot, several OSN uses authentication procedures such as CAPTCHA, multi-factor authentication, and photos-of-friend identification. For instance, the leading social networks like Twitter and Facebook use two-factor authentication principles. This principle uses a login password and a verification code received through a mobile device. This helps to mitigate the risk of an account being compromised and prevents an attacker from hijacking a legitimate account and posting malicious content.

Security and privacy setting

Many social networking sites provide configurable security and privacy setting to empower the client to shield their personal information from undesirable access by outsiders or applications. For instance, the Facebook client can modify their security setting and select the audience (like friends, friends of friends, and everybody) in the network who can see their details, pictures, posts, and other sensitive information. Moreover, Facebook additionally permits its users to either acknowledge or reject the access of third-party applications to their personal information. Many social networking sites are equipped with security measures that are internal to the system. They ensure users of the network against spams, counterfeit profiles, spammers, and different risks.

Report users

Online social networks protect the young generation and teenagers from being harassed by providing the facility to report any form of abuse or policy violations by any user in their network. For instance, if a user sees something on Facebook that is objectionable to the individual’s sentiments, but it doesn’t violate the Facebook terms then the user can utilize the report links to send a message to the one who posted it asking him to take it down or remove. When Facebook receives reports, it is reviewed and removed according to the Facebook community standards.

Academic research-based solutions

Phishing detection.

Phishing distresses the privacy and security of many traditional web applications such as websites, social networking sites, emails, and blogs. Consequently, several anti-phishing techniques have been developed to detect phishing attacks. Many researchers have put forward anti-phishing procedures which are based on techniques that try to identify phishing websites and phishing URLs. As phishing attacks are becoming more and more pervasive in online social networking sites, the research community has suggested specialized solutions for phishing attacks in a social networking environment. For instance, Aggarwal et al. proposed the PhishAri technique for real-time identification of phishing attacks occurring on Twitter. It utilized specific Twitter features like account age and number of followers to detect if the posted tweet is phishing or safe [ 16 ].

Cyberbullying detection

Although detecting cyberbullying is more complex than detecting racist language and spam [ 90 ], some researchers have tried to detect it using more complex document representation and additional information about victims and bullies [ 91 ].

Machine learning techniques can be applied to detect cyberbullying [ 92 ]. Rather than using only words and emoticons which expresses insults, obscenity, and typical cyberbullying words [ 93 ], it can also use some additional information like the gender and personality of the participants in a suspected cyberbullying event [ 94 ]. To deal with uncertainty and imprecision, a fuzzy rule-based system can be used which is a mathematical tool. To optimize the results genetic algorithms are the direct and stochastic methods.

For addressing the problem of online cyber grooming, machine learning techniques appear to be an effective measure. Michalopoulos et al. [ 18 ] presented the Grooming Attack Recognition System (GARS) a technique to recognize, analyze and control grooming attacks so that children could be protected against online attacks. It calculates the total risk value which identifies grooming threats to which a child is exposed by analyzing conversations by the child. A threshold is predefined for risk value and when the total risk value crosses the predefined threshold, an alarm mechanism is prompted. This alarm mechanism also simultaneously transmits an on-the-spot warning message to the parent. A colored signal is generated to warn the child about the degree of danger in a conversation. Escalante et al. [ 95 ] evaluated the use and performance of a profile to detect sexual predators. Through this evaluation, they also investigated aggressive texting.

Balduzzi et al. [ 19 ] designed and developed an automated system that can analyze web pages to protect the user against clickjacking attacks. It consists of a code that can detect overlapping clickable elements. And in addition to this solution, they also adopted the NoScript tool, which has an anti-clickjacking feature included in it. Anas et al. [ 96 ] proposed a solution in which other visual components are added which guarantees that the user is not able to proceed with his actions until and unless he has visibility over the control in place. To enable the working of this solution, the existence of a HyperText Markup Language (HTML) object containing a pattern was ensured. Some checkpoints are generated based on user interaction. User must follow those checkpoints without a single mouse click. In addition to it, a panel area shows the third-party reference identity. And to ensure the integrity of actions, user interface verification control is used. This technique can be applied in two ways, one is by generating random patterns in which the user has to follow that pattern to further propagate his action and the other way is to ask the user to draw that specific pattern which he has already registered. Microsoft introduced X-FRAME-OPTIONS, an Hyper Text Transfer Protocol (HTTP) header sent on HTTP responses, as a defense against frame busting and clickjacking in Internet Explorer 8. JavaScript can also be used as a defense against clickjacking [ 97 ].

Encryption techniques are available for devices on recent versions of Android and iOS. If a device is stolen, the thief cannot read the contents if encryption is enabled. Further, any attempts to read the information from internal or external memory is thwarted by the existence of a device password [ 98 ]. There are various technologies which can be used against stalkers like smartphone fingerprint lock antivirus, specialized stalker app detection software, firewalls, and privacy guards. Device encryption can be used against spyware, stalker apps and device theft [ 98 ]. Frommholz et al. have described machine learning techniques for detecting cyberstalking using textual analysis altogether [ 99 ].

Cyber espionage is a kind of targeted attack. Sahoo et al. described the concept of an ATA detection framework and introduced a system design checklist which is explicitly designed for identifying targeted attacks [ 20 ]. Organizations can create their own team to fight against targeted attacks and analyze vulnerabilities, in their and as well as in other companies’ code. Google has its own team to analyze vulnerabilities and bugs in their code. Each company has its own profile that is different from each other. So, each company must take appropriate steps according to their profile to implement security measures to design and implement security controls to address various security risks. Organizations can also be secured to some extent against targeted attacks by means of authentication systems. Earlier only password was used to protect the data, but now a two-factor authentication system is used which is a combination of password and some pin or biometric details. It is more secure than using a single factor i.e. password. The data which is no longer required for business purposes should be removed from the company's network. Keeping those records may create the risk of unauthorized access to sensitive information in an organization [ 100 ].

Fake profile

The author in Ref. [ 101 ] describes one model to distinguish the counterfeit accounts and profiles. They extracted some user profile contents from LinkedIn platform and processed those profiles content to extract different features. Subsequent to preprocessing of profiles through principal component, a training set is created utilizing the resilient backpropagation algorithm in a neural network. Support Vector Machines (SVMs) is utilized for characterization of profile. The author in Ref. [ 102 ] proposed a model that detects bot net using adaptive multilayered-based machine learning approach. The proposed work presented a bot detection framework based on decision trees which effectively detects P2P botnets. Also, the author in Ref. [ 103 ] proposed an ensemble classification model for the detection of fake news that has achieved a better accuracy compared to the other state-of-the-art. The proposed model extracts important features from the fake news datasets, and the extracted features are then classified using the ensemble model comprising of three popular machine learning models namely, decision tree, random forest, and extra tree classifier. Furthermore, the author in Ref. [ 104 ] presented a systematic literature review of existing clone node detection schemes with some theoretical and analytical survey of the existing centralized and distributed schemes for the detection of clone nodes in static WSNs environment.

Sybil detection

Al-Qurishi et al. [ 105 ] proposed a new Sybil detection system that uses a deep learning model to predict a Sybil attack accurately. This model consists of three modules namely, one data harvesting module, one feature extracting module and a deep regression model. All these three modules work in a systematic form together to analyze a user’s profile on Twitter. Rahman et al. gave a model named SybilTrap which is a graph-based semi-supervised learning system that uses both content-based and structure-based techniques to detect Sybil attacks. It is based on a semi-supervised algorithm which utilizes the interaction graph information of a node where labeled information of nodes flows through unlabeled nodes. It gathers information about the network and its users and uses this information to detect malicious users. This system is resistant to various strategic attacks such as targeted or random attacks. It is designed to work under any condition and is applicable to all existing social networks regardless of their level of trust [ 21 ].

Spam detection

Rathore et al. proposed a framework called SpamSpotter to solve the issue of spam attack on Facebook. It is based on the intelligent decision support system (IDSS). It gathers all relevant information from the user profile with the help of a decision process in IDSS and then analyzes it by mapping user data to the classification of a user profile as a spammer or legitimate. It resolves some of the issues and challenges (1) It solves the issue of an inadequate set of features that exist in most of spammer detection system. (2) It resolves the issue of uncertainty about critical pieces of Facebook information and public unavailability. (3) The use of the IDSS system resolves the issue of low accuracy and high response time. The use of machine learning classifiers in IDSS provides fast response time that is very essential to detecting spam on Facebook [ 17 ].

Faghani and Saidi [ 106 ] found that the visiting behavior of the social network members affects the propagation of XSS worms. The worm propagates slower when members mostly visit their friends rather than strangers. It can also be slowed down by the clustered nature of social networks. This is so because infected profiles in the early stages of XSS worm propagation lead to faster propagation of worm. Xu et al. [ 22 ] developed an approach to detect worms which leverages properties of online social network and propagation characteristics of OSN worms. It first builds a surveillance network based on the properties of the social graph to gather evidence against suspicious worm propagation. It monitors only a small fraction of user accounts to maximize surveillance coverage. To ensure that noise is absent in a surveillance network, a scheme is further proposed. Table 3 represents the probability of encountering different types of threats in different platforms discussed in “ Introduction ” section. It shows that the platforms used for social connections are the most vulnerable among all platforms.

Other contributions

The author in Ref. [ 107 ] proposed a novel algorithm to reform any traffic domain into a complex network using the principles of decentralized Social Internet of Things (SIoT). With the help of social networking, concepts integrate into the Internet of Things (IoT), the concept of SIoT has been proposed. The idea of the article is, every vehicle acts as a smart thing, communicate with nearby vehicles within a particular distance in a decentralized manner and together form a complex network. Also, the author in Ref. [ 108 ] proposed propose a privacy-preserving ICN forwarding scheme based on homomorphic encryption for wireless ad hoc networks to protect the private information of the user. The trust-based model proposed by the author in Ref. [ 109 ]. The author proposed a secure trusted hypothetical mathematical model for ensuring secure communication among devices by computing the individual trust of each node. In addition to this, the author proposed a decision-making model, that integrated with the hypothetical model for further speeding up the real-time communication decision within the network.

Comparative analysis with other state of art techniques

This section compared our survey related to different threat analysis and their defensive approaches with other state of art techniques and survey to show the novelty shows in Table 4 .

Security-guidelines for OSNs user

Nowadays, online social media and network have become an integral part of everyone’s life. As the reputation of these social sites grows, so do the risks of using them. The number of users increases exponentially every year. So, it becomes a necessity to secure users on these platforms. Below are some security-guidelines for users which they can practice keeping themselves reasonably secure. We have tried to give security-guidelines in two ways. First, it has been described in a general form and then it is described platform-wise (as shown in Fig.  10 ).

Security guidelines for users

General guidelines

Use a strong password: for maintaining the security of accounts, users should choose a strong password. It should not be too short as short passwords can be easily guessed. It should be long enough and must contain alphanumeric values with some special characters [ 119 ]. Users should not use the same password which they use for other accounts because if somehow an attacker gets to know that password, he can compromise all accounts of that user. So, choosing a strong password can help a user safeguard their account and profile from unauthorized access [ 120 ].

Limit location sharing: nowadays sharing location has become a trend. Many social networking sites have also introduced the feature of geotagging which automatically tags the geographical location of the user when the user uploads any multimedia on social media [ 121 ]. The user has to switch it to manual so that it does not tag location automatically. Sharing location online makes a user vulnerable to real-life crimes like robbery. So, to mitigate this risk, the user can post his location at a later point of time post completion of the visit [ 122 ]. Users must upload their multimedia content online very carefully as it may contain sensitive metadata and it is recommended to switch geotagging to manual mode in all their mobile devices and accounts. Also suggested is the use of software that removes such metadata from the pictures before uploading.

Be selective with friend requests: it is seen that many users accept friend requests without analyzing the complete profile of the requester. People generally accept friend request based on mutual friends. If the requester has some mutual friends, then they accept it [ 123 ]. Sometimes attackers make their profile attractive deliberately or they may impersonate an account. So, if the person sending a friend request is unknown, one should ignore that friend request. It could be a fake account attempting to steal sensitive information.

Be careful about what you share: users should be careful about their posts as it may reveal their personal information and sometimes others also. Many organizations keep strict rules and regulations for sharing information and multimedia content. There are many reports of people getting fired from their job due to sharing information illegally. This situation can be avoided if employees are well informed about the protocols of the organization they are working in regarding pictures, videos, and messages that they post online. Sharing information illegitimately can harm an organization’s reputation in the market along with its data and intellectual property also.

Be aware of links and third-party applications: illegitimate users can get access to someone’s account and get sensitive information by sharing a malicious link. Nowadays shortened URLs are becoming very popular on various social media platforms. These shortened URLs may be obfuscated with malicious code or script. These scripts try to gather the personal and confidential information of a user which may breach the privacy of that user. Moreover, hackers may take advantage of vulnerabilities present in a third-party application that is integrated with many popular social networks [ 124 ]. An example of such a third-party application happens to be games that are playable on online social networks which ask for user’s public information to consume their services. This gathered information may be provided to outsiders or third-party interventions. To avoid this risk, user should be careful while installing third-party applications in their profile.

Install internet security software: some threats whose pattern is known may easily be detected through anti-viruses. Threats like cyber grooming, cyberbullying can be detected to some extent by using anti-virus software [ 125 ]. Many malicious links can be shared by our friends unknowingly which redirects the user to some phishing website. Anti-virus software should be kept updated regularly due to the presence of many viruses created by hackers on a daily basis. Some social networking sites also have their own security tools which can be used by users to protect themselves from cyber-attacks.

Platform-wise

For professional networks.

Professional networks are primarily used to create contacts and increase perceptibility to potential recruitment companies [ 126 ]. So, to be safe on professional networks, one should look for the details provided by other users before adding them to one’s contact list. Generally, an adversary does not provide many details about his career.

A user should check if there are any spelling or grammar mistakes in someone's profile because if someone is applying for some job, it should be very well written and should be free from any spelling or grammar mistakes [ 127 ]. It should contain good information about that person.

Checking for consistency in a person’s career can be a good practice if a user wants to be safe on a professional network. A profile which continually and definitely changes over a short span of time is the most used part as a draw by the invader. At the point when the fraudster needs to target one sort of organization or vertical, he simply adds a new position that could be pertinent to his targets.

One should also cross-check information. If a person claims to be from the employer’s company, the user can check the company’s directory and should not hesitate to verify from his company’s human resource department.

For multimedia sharing platform

One should not post sensitive information in their photos or caption [ 3 ]. Exposing too much private information in a profile can be dangerous.

Sharing current locations on social media should be avoided. Geotagging services provided by different multimedia platforms should be turned off manually. There have been plenty of cases of thieves that were tipped off to rob homes. Suspects use social media to gather information about victims who share their location online. People who leave for a short holiday and brag about it online may come home to find the place emptied.

If an application is not in use for a long period, it is better to revoke access to that application. There are so many third-party applications which use social media account to log-in. For security and privacy concerns, one should allow access to applications that are trustworthy [ 4 ].

Enable two-step authentication for all your social media accounts wherever possible. This provides an extra layer of security to the account. In case an adversary finds out the password of a user, he will still need a second factor to authenticate himself. The second factor consists of a unique, time-sensitive code that users receive via text on their mobile phone.

For social connection platform

Users should learn about the privacy and security setting for different social media platforms and use them [ 128 ]. Each platform has its own privacy and security setting. Every platform provides settings, configuration, and privacy sections to limit who and what groups can see various aspects of the user’s profile. The privacy setting provided by the sites as default should not be adopted as it is.

The more details provided, the easier it is for an adversary to use that information to steal identity or to commit other cybercrimes. Thus, information sharing should be limited.

Before accepting a friend request, one should completely check the profile of the requester. One can make different groups for sharing different kinds of information like a different group for colleagues and family.

Before posting any information on the profile, employees should know their company’s policy over sharing any content online on social networks.

For discussion forums

One should pay attention while clicking on links given by various authors. It may be some suspicious site trying to get the credentials of the user.

Users should always keep an eye on the site’s URL. Noxious sites may look compellingly indistinguishable from a real one, however, the URL may contain slight inconsistencies like the variety in spelling or an alternate domain (e.g., .com versus.net) [ 129 ].

Be careful about communications that requests the client to act promptly, offers something that sounds unrealistic or requests personal information.

Open research issues and challenges

Scientists and researchers have found many methods and solutions to secure users on social media but there are still some issues which are not resolved. In this section, we discuss some of those issues and challenges.

Unfortunately, social networking sites are the easiest way for an attacker to lie about his identity and target the victim. They can lie about their age, looks, and can project themselves as a completely different identity according to their target. Child predators are taking advantage of this drawback in social networking sites, as children are a very easy target on these social platforms. These platforms have millions of users and monitoring each user can be very difficult. Therefore, there is a need for some system which can detect child predators effectively. Although the research community is trying to solve this issue, we need a good and effective system which can stop cyber grooming more efficiently. One possible addition to the already existing systems would be to incorporate artificial intelligence. The chat system can be improved to analyze conversations and derive meaningful inferences to support decision-making.

Social networking sites make money by allowing other companies to show advertisements on their website. Every time a user clicks an advertisement, it takes the user to a page where the user can buy a product and the social networking site get a percentage of that sale. These sites collect data of the users each time they use them so that they can show the advertisements as per the user’s interest. In this way, these social networking sites are collecting a huge amount of personal data of the user which can be sold to hundreds of businesses without user's knowledge. Hence, the user’s personal data is at risk. One possible way to thwart such data leaks is to inform the user of the data being shared. This would involve non-technical aspects to enforce a law or contract that all advertisements should abide by. From a technical standpoint there is not much control as to what the parent site decides to share with the advertising agency. Client-side browser restrictions could also provide wrapper-level security.

Nowadays surveys and games are becoming very popular on social media [ 130 ]. Generally, these surveys involve entering credentials which are supposed to enable the data for the survey to be gathered or the results to be shared. And while these surveys are collecting credentials, adversaries can skim those details to compromise user’s account.

Due to character count limitations on Twitter, people use shortened URLs to share their multimedia content. Adversaries can easily obfuscate malicious sites on these shortened URLs. This is an alarming situation since other social media applications like WhatsApp also have users who have started sharing shortened URLs. However, some social networking sites are working on this issue and have given solutions, but it is as yet conceivable that URL redirection can be used to hop from a safe landing point to a risky landing point. Again, a central repository of phishing sites could be leveraged by the client browser to warn the user when landing on the suspicious website. Further research could be conducted towards preemptive solutions that can parse URLs and warn the user even before clicking. A system is needed which can detect the malicious site from the shortened URLs effectively leveraging the already existing solutions.

Business-oriented networks contain significant business data that can be utilized to perform social engineering attacks. Some LinkedIn invitation update messages have been referred to be utilized as URL redirectors which can divert clients to some vindictive pages. This issue should be resolved so that users can be protected from a targeted attack. Here, intelligent language parsers could be trained to detect sensitive information and warn the originator of the information. Content detection can be applied to such platforms to find malicious activity. It can detect the number of posts posted through a profile because generally, the adversary posts similar messages.

There is a need to secure users on discussion forums also. Users can be easily fooled on discussion forums through phishing attacks which could result in deteriorating user trust on these forums. URL detection and filtering can be applied for these forums also to protect a user from malicious activity. Although such scenarios usually inform the user that they are moving out of the parent domain. The cost to reward ratio here is poor for any forum to implement parsers to parse external links. An incentive-based solution can be thought of to reward sites that scan external links.

Online social networks have become a vital part of the vast internet penetrated world. The paradigm shift has enabled social networks to engage with users on a daily basis. The increased rate of social media usage has solicited the need to make its users aware of the pitfalls, threats, attacks, and privacy issues in them. With the advancement in technology, social media has taken various forms. Individuals can connect to each other in a myriad of ways. Through professional sites, discussion forums, multimedia sharing networks, and many more, netizens can find themselves at the pinnacle of connectivity. Unfortunately, lack of awareness among users regarding security and privacy has the potential to lead to various cyber-attacks through social media. Although academia has come up with innovative solutions to address the security measures that are concerned with social media security, they suffer from a lack of real-world implementation and feasibility. Thus, there is a compelling need to continuously and iteratively review security issues in social networks keeping in pace with technological advancement. In this paper, we presented different scenarios related to online social network threats and their solutions using different models, frameworks, and encryption techniques that protect the social network users against various attacks. We have outlined different solutions and comparative analysis of different survey for better clarity about our survey. However, many of these privacy issues are not yet resolved. In addition to the defensive solutions, parents must monitor the kids actively when they are using internet services like OSNs. Overall, researchers can play a significant role in the defensive approach against these attacks in OSNs but still, some issues need to be resolved by using some hybrid approach, framework, and threat detection tools.

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Jain, A.K., Sahoo, S.R. & Kaubiyal, J. Online social networks security and privacy: comprehensive review and analysis. Complex Intell. Syst. 7 , 2157–2177 (2021). https://doi.org/10.1007/s40747-021-00409-7

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The Relationship Between Networking, LinkedIn Use, and Retrieving Informational Benefits

1 Department of Social Media, Leibniz-Institut für Wissensmedien, Tübingen, Germany.

2 Department of Psychology, University of Tübingen, Tübingen, Germany.

Johannes Breuer

3 Department of Data Linking and Data Security, GESIS Leibniz Institute for the Social Sciences, Colonge, Germany.

Previous research has shown that users of social network sites designed for professional purposes, such as LinkedIn , report higher professional informational benefits than nonusers. However, this effect could only be partly explained by social media use as there was also a selection effect, such that people who have more informational benefits were more likely to use LinkedIn . The goal of this study was to explore whether differences in networking, defined as a set of behaviors with the aim of building, maintaining, and using internal and external contacts for instrumental purposes, can explain this selection effect. We used data from a panel study with a representative sample of Dutch Internet users ( n  = 685; 259 LinkedIn users) to examine the relationships between networking and LinkedIn use as well as professional informational benefits, that is, timely access to relevant information. The results showed that people scoring high on external networking (but not internal networking within their organization) are also more likely to use LinkedIn . External networking was also positively correlated with active and passive use as well as the number of strong and latent ties on LinkedIn . However, in a mediation model the direct effect of networking on informational benefits was not mediated by actual social media use and network composition; instead, the number of weak ties had a direct effect on informational benefits. The results thus indicate that networking is a major driver of informational benefits from LinkedIn use.

Introduction

Research on social networking sites (SNS) designed for professional purposes (professional networking services [PNS]), 1 such as LinkedIn or Xing , has shown that users of these platforms report higher informational benefits, that is, (timely) access to resources and referrals to career opportunities, than nonusers do. 2 , 3 However, these studies also revealed that only a small percentage of the variance in informational benefits could be explained by social media use. There was also a selection effect, such that people who already had more informational benefits were more likely to use these platforms. The goal of this article is to bring together research on PNS and research from organizational psychology to test whether networking is the variable that could explain this selection effect. Networking is a concept from organizational psychology and defined as building and maintaining informal relationships that might give access to information and resources. 4 So far, research on networking in professional settings did not pay special attention to the role of the medium; a recent review 5 even explicitly excluded studies that focused on SNS. Research on SNS, however, focused mainly on personality traits, such as the Big Five or narcissism, when looking for predictors of social media use, 6–8 but did not consider networking as a key variable. We aim to enrich both streams of literature by examining the role of networking behavior in using and retrieving informational benefits from LinkedIn.

Networking is defined as a set of behaviors aimed at building and maintaining interpersonal relationships that possess the (potential) benefit to facilitate work-related activities by providing access to resources and jointly maximizing advantages of the individuals involved. 4 Researchers commonly distinguish between internal networking with colleagues in one's own organization and external networking with people from other organizations. 9

Wolff et al. provide a model of the antecedents and consequences of networking. 10 They list demographic variables, structural variables (e.g., job function), and individual characteristics (e.g., personality) as antecedents and divide the consequences into individual and organizational benefits (job performance). Individual benefits are further differentiated into access to primary (work-related support and strategic information) and secondary (career success, visibility, and power) resources. Several retrospective, cross-sectional, and prospective studies have focused on the secondary resources and demonstrated that networking can lead to subjective (e.g., career satisfaction) or objective (e.g., promotion) career benefits. 5 , 11 , 12 The effects of networking on informational benefits as primary resource, however, received considerably less attention.

For our study, we define and operationalize informational benefits as (timely) access to work-related information and referrals to career opportunities. 13 Based on the model by Wolff and Moser, 10 a positive relationship between networking and informational benefits can be expected. There is also indirect support for this assumption because several studies could show that networking is positively related to career outcomes, 11 , 12 , 14 and that access to information predicts positive career outcomes. 15

H1: Networking is positively related to informational benefits.

The relationship between networking and social media use

Research focusing on Facebook or other SNS mainly used for leisure purposes generally found that most users maintain existing relationships rather than build new relationships. 16 Compared with Facebook , PNS such as LinkedIn or Xing are explicitly designed for professional networking. 17 Hence, using these platforms represents a very specific form of online networking behavior. We, therefore, assume that networking is positively related to using LinkedIn . In contrast to company-internal enterprise social networks, platforms such as LinkedIn allow people also to connect with others across organizational boundaries. Most people on professional SNS have more connections with people from different organizations but the same field than with colleagues from their own company. 18 We, therefore, expect a positive relationship between external networking and LinkedIn use, but also want to explore whether internal networking might predict LinkedIn use as well.

H2: People scoring high on external networking are more likely to use LinkedIn .

RQ1: Are people scoring high on internal networking more likely to use LinkedIn?

Networking and informational benefits retrieved from professional SNS use

In the next step, we want to examine whether people scoring higher on external networking are not only more likely to use LinkedIn , but also to use it in a way that further increases informational benefits. Basically, two effects could be expected. First, networking might be related to the size and composition of the LinkedIn network. Second, networking might also be related to actual LinkedIn use.

Since networking is defined as building and maintaining contacts, we also expect people scoring high on external networking to have a larger number of contacts. First, they probably already have larger offline networks when they start using LinkedIn , which should be mirrored in their online networks. Second, we assume that people who score high on external networking also use social media platforms more for making new contacts, for example, by reacting to contact recommendations made by the platforms. Reacting to such recommendations often creates so-called latent ties, which are ties that are “technologically possible but not yet activated socially.” 19 (p137)

H3: External networking is positively related to the number of strong, weak, and latent ties on LinkedIn .

It is less clear whether people scoring high on networking also use LinkedIn in a way that is beneficial for retrieving informational benefits. People scoring high on networking engage in various offline activities, such as attending conferences or going for a beer with colleagues. Hence, we expect that they also use LinkedIn in an active way. In previous empirical studies, posting professional content and activity in groups turned out as predictors of informational benefits. 2 , 3 Research on enterprise social media as well as on LinkedIn argued and found that passive use, that is, reading or skimming social media updates is positively related to building ambient awareness, a cognitive representation of who knows what, which is an antecedent of retrieving informational benefits. 20–22 People engaging in networking behavior usually want to be well informed about what is going on in the field. Accordingly, we also expect a positive relationship with passive LinkedIn use.

H4: External networking is positively related to (a) active and (b) passive LinkedIn use.

In a last step, we examine whether social media use and network composition partly or fully mediate the effect of external networking on informational benefits. This would be a first hint that people scoring high on external networking have higher informational benefits because they use PNS in a more efficient way. If there is an independent effect of networking behavior, this could imply that, although online platforms are used as additional channels, the informational benefits are obtained outside of them (i.e., offline).

RQ2: Do network composition and LinkedIn use mediate the effect of external networking on informational benefits?

Sample and procedure

We used a subsample of working people ( n  = 685; 262 women, 423 men; age: 13.4 percent between 18 and 29, 20.7 percent between 30 and 39, 25.8 percent between 40 and 49, 34.7 percent between 50 and 64, and 5.3 percent older than 65) from wave 6 from a larger longitudinal study of Dutch Internet users (eight waves with a time interval of 6 months; see https://www.redeftiedata.eu/ for all measures and data). Among those, 43 percent ( n  = 297) reported that they use PNS; in most cases, this was LinkedIn ( n  = 259).

LinkedIn use

We asked participants whether they used LinkedIn or another PNS. For this article, we focused on people who use LinkedIn .

Passive and active LinkedIn use

To measure frequency of passive use, we asked LinkedIn users how often they read posts. For frequency of active use, we assessed how often they posted on LinkedIn . Answers were given on a scale from (1) “never” to (5) “very often.” One item specifically addressed activity in groups on a scale from (1) “not at all” to (5) “regularly.” In addition, we assessed posting professional content by asking respondents how often they post about professional success, general information about work, or ask for job-related advice on five-point scales ranging from (1) “never” to (5) “very often” (5). Cronbach's alpha for this three-item scale was 0.87.

Network composition

Respondents were told that it would be helpful to open their account in another window or tab of their browser for answering the network questions. They first reported the overall number of contacts they have. After reading a brief description of strong and weak ties, they were asked to estimate how many of those are strong or weak ties, respectively, and how many they would not even recognize when they meet them on the street (to capture the even weaker latent ties). Since these numbers showed severe skewness and kurtosis, we log-transformed them using the formula ln(x + 1) to avoid missing values for people who reported zero ties.

Professional informational benefits

We used five items from the scale by Wickramasinghe and Weliwitigoda. 23 Respondents indicated their agreement on five-point scales ranging from (1) “strongly disagree” to (5) “totally agree” (5). Cronbach's alpha for this scale was 0.89.

Networking was assessed with nine items on networking within one's own company (internal networking, Cronbach's α = 0.90) and nine items on networking with people outside one's own company (external networking, Cronbach's α = 0.95). 24

Descriptives and correlations

The descriptives and zero-order correlations for internal and external networking, informational benefits, LinkedIn use indicators, and network composition are presented in Table 1 .

Descriptives and Intercorrelations of the Central Variables

The means for strong, weak, and latent ties are based on the untransformed values; the correlations are based on the log-transformed values.

As can be seen in Table 1 , both, external and internal networking, were positively correlated with informational benefits. Hypothesis 1 is thus supported. The correlations also provide some support for H3. External networking was positively related to the number of strong and latent ties, but not to the number of weak ties. Also, H4 was largely supported by the correlation analysis: External networking was positively related to frequency of reading (H4a), activity in groups and posting professional content (H4b). Only the correlation with frequency of posting was not significant ( p  = 0.061).

Networking and LinkedIn use

To test H2 and answer RQ1, we conducted a logistic regression with using LinkedIn (no/yes) as criterion and internal and external networking as predictors. This analysis only revealed a significant effect for external networking, Exp(B) = 1.53, 95 percent confidence interval (CI) [1.20–1.95], Wald = 11.98, p  < 0.001. H2 is thereby supported. The answer to RQ1 is that internal networking is not related to LinkedIn use, Exp(B) = 1.12, 95 percent CI [0.84–1.49], Wald = 0.62, p  = 0.433.

Indirect effects of external networking on informational benefits

To answer RQ2, we ran a mediation model using PROCESS 25 model 4. External networking was the independent variable, informational benefits the dependent variable, and frequency of reading, activity in groups, professional content as well as number of strong, weak, and latent ties (log-transformed) were the predictors. We did not include frequency of posting since the correlation analysis showed that it was unrelated to networking and informational benefits ( Table 1 and Fig. 1 ).

Results of the Process Model (Hayes 25 ) testing for indirect effects of external networking on informational benefits (unstandardized effect sizes).

The mediation analysis revealed, again in line with H1, a direct effect of external networking on informational benefits, 0.38, standard error ( SE ) = 0.06, 95 percent CI [0.26–0.50]. As in the correlational analysis, networking was positively related to frequency of reading, activity in groups, posting professional content, and number of strong and latent ties in this more complex model (see Fig. 1 for coefficients and CIs). However, none of the indirect effects was significant because the relationships between the various indicators of LinkedIn use and network composition and informational benefits were weaker when controlling for external networking. Only the direct effect of number of weak ties on informational benefits was significant: 0.16, SE  = 0.05, 95 percent CI [0.06–0.25]. The answer to RQ2 is, hence, that LinkedIn use and network composition do not mediate the effect of external networking on informational benefits.

The aim of this article was to bring together research on PNS and research on networking behavior to explore whether networking behavior is related to LinkedIn use and the informational benefits derived from PNS use. The results show that people scoring higher on external networking are more likely to use LinkedIn as a tool for managing their networks. External networking was also positively related to passive and active use of LinkedIn , as well as to the number of strong and latent ties. Whereas the LinkedIn use indicators and the network variables (with the exception of posting frequency) were positively correlated with informational benefits, in the mediation model only external networking and number of weak ties remained as significant predictors.

Our results have implications for several domains. First, we extend prior research on social media use by introducing a new predictor from organizational psychology. We demonstrate that this makes sense in the context of professional networking: external but not internal networking predicts the likelihood of using LinkedIn . Within the group of LinkedIn users, networking was further positively related to passive and active use as well as the number of strong and latent ties. Whereas it has been argued that SNS such as Facebook are mainly used for maintaining existing relationships but not for building new relationships, 16 we find that LinkedIn is also used for extending networks as indicated by the high number of latent ties.

On the correlational level, we also replicated prior findings on the relationships between passive (reading) and active use and informational benefits. 2 The correlation between reading and informational benefits fits with theoretical work on ambient awareness. 21 , 26 Passive social media use is often regarded as having negative consequences, for example, for life satisfaction. 27 However, our findings suggest that the quality of these effects strongly depends on the domain. Professional informational benefits are positively related to career satisfaction, which is also a determinant of overall life satisfaction. 28 Future research should examine whether and how PNS use contributes to career satisfaction and, thus, potentially also overall life satisfaction.

Interestingly, the effects of the LinkedIn use indicators were no longer significant when all predictors were included in one mediation model. Instead, external networking had a direct effect on informational benefits. Earlier work has found that LinkedIn use explains only a part of the variance in informational benefits. This research indicates that networking might be the crucial variable that explains why LinkedIn users report higher informational benefits. A reason for the smaller relationship between LinkedIn use and informational benefits when controlling for external networking might be that many informational benefits are obtained in offline situations, such as conferences or social events. Using LinkedIn could also be a proxy for a stronger career orientation or working in a sector in which information and referrals are very important.

Interestingly, the number of weak ties was not correlated with external networking, but predicted informational benefits independently of networking. Thus, we find support for the assumption that weak ties provide access to nonredundant information, 29 and show that using LinkedIn for keeping in touch with weak ties also benefits people who do not score high on external networking. It is still puzzling that external networking was positively correlated with the number of strong and latent ties, but unrelated to the number of weak ties. This finding could be due to the particular measure we used. It might, however, point to an important difference between skilled networkers and people who network less: Whereas it seems common to add weak ties, such as former colleagues, on LinkedIn , regardless of one's networking skills, people who frequently engage in networking seem to focus more on the other types of ties. On the one hand, they are more likely to strategically add people that might become useful at some point of time (latent ties). On the other hand, they might report a higher number of strong ties because they also leverage their networks more frequently and, therefore, interact more frequently with more people (the correlations with active use support this notion). To further explore this explanation, it might be valuable to investigate this in future research using more detailed network measures. As the survey was part of a larger study also including Facebook and Twitter use, and many people have several hundreds of LinkedIn contacts, it was not feasible to assess tie strength for each and every contact.

Our study also extended prior research on networking that mostly focused on indicators of career success by looking at informational benefits, thereby testing another part of the model by Wolff et al. 10 We found that both, internal and external networking, correlated with informational benefits. However, only external networking predicted LinkedIn use. This shows the value of the distinction between internal and external networking. This pattern can be explained by the affordances of the platform. LinkedIn explicitly promises its members to connect them with professionals from all over the world. These are mainly external contacts, so external networking is the better predictor of using this platform. Future research could examine whether internal networking predicts the (frequency of) use of enterprise social media.

Before closing, we would like to note the strengths and limitations of the study. A limitation is that we had single items measures for reading and activity in groups because the data are part from a larger survey covering a variety of topics related to SNS use. The number of strong, weak, and latent ties is also a somewhat crude proxy of network structure. The finding that networking is unrelated to the number of weak ties could thus be due to the operationalization. Future research should use measures of network structure (e.g., density, bridging ties). A key strength of our study is that our sample is largely representative for Dutch online users. We assume that the general pattern also holds for other Western countries because positive effects of networking on organizational outcomes have been found for German and American samples 11 , 12 , 14 ; what might differ is the social media platform use. In German-speaking countries, Xing is more popular than LinkedIn . 18

Taken together, this is the first article to bring together research on PNS and research on networking behavior. The results show that networking is a promising variable when it comes to social media use in the professional domain.

Acknowledgment

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 312420.

Author Disclosure Statement

No competing financial interests exist.

Networking is central to modern computing, from WANs connecting cell phones to massive data stores, to the data-center interconnects that deliver seamless storage and fine-grained distributed computing. Because our distributed computing infrastructure is a key differentiator for the company, Google has long focused on building network infrastructure to support our scale, availability, and performance needs, and to apply our expertise and infrastructure to solve similar problems for Cloud customers. Our research combines building and deploying novel networking systems at unprecedented scale, with recent work focusing on fundamental questions around data center architecture, cloud virtual networking, and wide-area network interconnects. We helped pioneer the use of Software Defined Networking, the application of ML to networking, and the development of large-scale management infrastructure including telemetry systems. We are also addressing congestion control and bandwidth management, capacity planning, and designing networks to meet traffic demands. We build cross-layer systems to ensure high network availability and reliability. By publishing our findings at premier research venues, we continue to engage both academic and industrial partners to further the state of the art in networked systems.

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Social Networking Sites and Addiction: Ten Lessons Learned

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• 1 Psychology Department, International Gaming Research Unit, Nottingham Trent University, 50 Shakespeare Street, Nottingham NG1 4FQ, UK. [email protected].
• 2 Psychology Department, International Gaming Research Unit, Nottingham Trent University, 50 Shakespeare Street, Nottingham NG1 4FQ, UK. [email protected].
• PMID: 28304359
• PMCID: PMC5369147
• DOI: 10.3390/ijerph14030311

Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning online social networking sites and addiction based on the insights derived from recent empirical research will be presented. These are: (i) social networking and social media use are not the same; (ii) social networking is eclectic; (iii) social networking is a way of being; (iv) individuals can become addicted to using social networking sites; (v) Facebook addiction is only one example of SNS addiction; (vi) fear of missing out (FOMO) may be part of SNS addiction; (vii) smartphone addiction may be part of SNS addiction; (viii) nomophobia may be part of SNS addiction; (ix) there are sociodemographic differences in SNS addiction; and (x) there are methodological problems with research to date. These are discussed in turn. Recommendations for research and clinical applications are provided.

Keywords: FOMO; addiction; dating; gaming; microblogging; nomophobia; recommendations; smartphone addiction; social media; social networking sites.

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• Behavior, Addictive / epidemiology*
• Psychological Distance
• Smartphone / statistics & numerical data
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Researchers detect a new molecule in space

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New research from the group of MIT Professor Brett McGuire has revealed the presence of a previously unknown molecule in space. The team's open-access paper, “ Rotational Spectrum and First Interstellar Detection of 2-Methoxyethanol Using ALMA Observations of NGC 6334I ,” appears in April 12 issue of The Astrophysical Journal Letters .

Zachary T.P. Fried , a graduate student in the McGuire group and the lead author of the publication, worked to assemble a puzzle comprised of pieces collected from across the globe, extending beyond MIT to France, Florida, Virginia, and Copenhagen, to achieve this exciting discovery. 

“Our group tries to understand what molecules are present in regions of space where stars and solar systems will eventually take shape,” explains Fried. “This allows us to piece together how chemistry evolves alongside the process of star and planet formation. We do this by looking at the rotational spectra of molecules, the unique patterns of light they give off as they tumble end-over-end in space. These patterns are fingerprints (barcodes) for molecules. To detect new molecules in space, we first must have an idea of what molecule we want to look for, then we can record its spectrum in the lab here on Earth, and then finally we look for that spectrum in space using telescopes.”

Searching for molecules in space

The McGuire Group has recently begun to utilize machine learning to suggest good target molecules to search for. In 2023, one of these machine learning models suggested the researchers target a molecule known as 2-methoxyethanol. 

“There are a number of 'methoxy' molecules in space, like dimethyl ether, methoxymethanol, ethyl methyl ether, and methyl formate, but 2-methoxyethanol would be the largest and most complex ever seen,” says Fried. To detect this molecule using radiotelescope observations, the group first needed to measure and analyze its rotational spectrum on Earth. The researchers combined experiments from the University of Lille (Lille, France), the New College of Florida (Sarasota, Florida), and the McGuire lab at MIT to measure this spectrum over a broadband region of frequencies ranging from the microwave to sub-millimeter wave regimes (approximately 8 to 500 gigahertz). 

The data gleaned from these measurements permitted a search for the molecule using Atacama Large Millimeter/submillimeter Array (ALMA) observations toward two separate star-forming regions: NGC 6334I and IRAS 16293-2422B. Members of the McGuire group analyzed these telescope observations alongside researchers at the National Radio Astronomy Observatory (Charlottesville, Virginia) and the University of Copenhagen, Denmark. 

“Ultimately, we observed 25 rotational lines of 2-methoxyethanol that lined up with the molecular signal observed toward NGC 6334I (the barcode matched!), thus resulting in a secure detection of 2-methoxyethanol in this source,” says Fried. “This allowed us to then derive physical parameters of the molecule toward NGC 6334I, such as its abundance and excitation temperature. It also enabled an investigation of the possible chemical formation pathways from known interstellar precursors.”

Looking forward

Molecular discoveries like this one help the researchers to better understand the development of molecular complexity in space during the star formation process. 2-methoxyethanol, which contains 13 atoms, is quite large for interstellar standards — as of 2021, only six species larger than 13 atoms were detected outside the solar system , many by McGuire’s group, and all of them existing as ringed structures.  

“Continued observations of large molecules and subsequent derivations of their abundances allows us to advance our knowledge of how efficiently large molecules can form and by which specific reactions they may be produced,” says Fried. “Additionally, since we detected this molecule in NGC 6334I but not in IRAS 16293-2422B, we were presented with a unique opportunity to look into how the differing physical conditions of these two sources may be affecting the chemistry that can occur.”

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Pennington Biomedical’s Dr. Steven Heymsfield and Colleague Publish Guidance on Energy and Macronutrients Across the Lifespan

April 17, 2024 · Baton Rouge, LA

In the growing campaign positioning “Food as Medicine,” Dr. Heymsfield joins Dr. Sue Shapses of Rutgers University to share a matrix of variables to consider when crafting nutrient-rich diets     BATON ROUGE – In the long history of recommendations for nutritional intake, current research is trending toward the concept of “food as medicine” – a philosophy in which food and nutrition are positioned within interventions to support health and wellness. In the paper – “ Guidance on Energy and Macronutrients Across the Lifespan ” – by Pennington Biomedical Research Center’s Dr. Steven Heymsfield, he shares the latest clarity and recommendations in the rich and storied history of energy and macronutrient intake.     The research paper by Dr. Heymsfield and colleague Dr. Sue Shapses, Professor of Nutritional Sciences at Rutgers University and Director of the Next Center at the New Jersey Institute for Food, Nutrition and Health, was recently published in the New England Journal of Medicine, showcasing recommendations with increased clarity for protein, fat, carbohydrates, fiber and water intake at various stages in the human lifespan.    "Couple with the amount and pattern of the foods people eat, the primary macronutrients of protein, carbohydrates and fat can shape the major determinates of health throughout the lifespan,” said Dr. Heymsfield, who is a professor of Metabolism & Body Composition at Pennington Biomedical. “Even considering the incredible diversity of traits and nutritional needs across the global population, we can potentially provide effective care for all patients, including the growing number of patients with diet-related diseases, so long as we recognize the subtle effects of the key macronutrients.”    Throughout the research document, the authors frequently reference the original, historic research for which they are providing the latest incarnation and related knowledge. Focusing primarily on energy and three macronutrients – protein, carbohydrates and fat, and their subsequent substrates – amino acids, glucose and free fatty acids, the paper shows how these can fuel growth and maintenance throughout life. For optimal health, the study provides dietary reference intakes for the three micronutrients at various stages: 0 to 6 months, 7 months to slightly less than a year old, one year to three, four to eight years, nine to 13 years, 14 to 18 years, over 19 years, and then additional recommendations for pregnancy and lactation.     The research goes on to provide recommendations to patients and caregivers on healthy eating patterns consistent with the energy and macronutrient guidelines and includes an online calculator ( https://www.nal.usda.gov/human-nutrition-and-food-safety/dri-calculator ). While the energy requirements and variable needs for the three main macronutrients and multiple micronutrients vary across the nine life stage groups, there are overarching nutritional goals for patients when choosing healthy food patterns. A variety of healthy meal pattern examples are available, but reoccurring components feature the inclusion of vegetables of all types, whole fruits, fat-free or low-fat dairy, lean meats, seafood, eggs, beans, and nuts, plant- and seafood-based oils, and grains, with at least half of those being whole grains.     The need to incorporate the three main macronutrient groups and micronutrients into the diets of the various life stage groups is a matrix that is further complicated as varying financial resources, personal preferences, cultural backgrounds and ethnic food traditions are accounted for. The paper structures a priority framework, offering better insights into those diets that can be tailored for specific diet-related chronic conditions, such as obesity or type 2 diabetes.     “The legacy of research into dietary nutrition continues to refine what we know about our bodies and the capacity for a tailored diet, featuring key macronutrients to support our long-term health,” said Dr. John Kirwan, Executive Director of Pennington Biomedical Research Center. “Dr. Heymsfield’s recent paper in the New England Journal of Medicine is the latest contribution to this research history of contributing to the knowledge base, and further promotes the notion of ‘food as medicine’ –  delivering the potential to improve health across the lifespan with bespoke, nutrient-rich diets.”

For more information contact:

Joe Coussan, Media Relations Manager, [email protected] , 225-763-3049 or Ernie Ballard, Senior Director of Communications & Marketing, [email protected] , 225-263-2677 .

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The Pennington Biomedical Research Center is at the forefront of medical discovery as it relates to understanding the triggers of obesity, diabetes, cardiovascular disease, cancer and dementia. The Center conducts basic, clinical, and population research, and is a campus of the LSU System. The research enterprise at Pennington Biomedical includes over 530 employees within a network of 44 clinics and research laboratories, and 13 highly specialized core service facilities. Its scientists and physician/scientists are supported by research trainees, lab technicians, nurses, dietitians, and other support personnel. Pennington Biomedical is a state-of-the-art research facility on a 222-acre campus in Baton Rouge. For more information, see www.pbrc.edu .

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How Pew Research Center will report on generations moving forward

Journalists, researchers and the public often look at society through the lens of generation, using terms like Millennial or Gen Z to describe groups of similarly aged people. This approach can help readers see themselves in the data and assess where we are and where we’re headed as a country.

Pew Research Center has been at the forefront of generational research over the years, telling the story of Millennials as they came of age politically and as they moved more firmly into adult life . In recent years, we’ve also been eager to learn about Gen Z as the leading edge of this generation moves into adulthood.

But generational research has become a crowded arena. The field has been flooded with content that’s often sold as research but is more like clickbait or marketing mythology. There’s also been a growing chorus of criticism about generational research and generational labels in particular.

Recently, as we were preparing to embark on a major research project related to Gen Z, we decided to take a step back and consider how we can study generations in a way that aligns with our values of accuracy, rigor and providing a foundation of facts that enriches the public dialogue.

A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations.

We set out on a yearlong process of assessing the landscape of generational research. We spoke with experts from outside Pew Research Center, including those who have been publicly critical of our generational analysis, to get their take on the pros and cons of this type of work. We invested in methodological testing to determine whether we could compare findings from our earlier telephone surveys to the online ones we’re conducting now. And we experimented with higher-level statistical analyses that would allow us to isolate the effect of generation.

What emerged from this process was a set of clear guidelines that will help frame our approach going forward. Many of these are principles we’ve always adhered to , but others will require us to change the way we’ve been doing things in recent years.

Here’s a short overview of how we’ll approach generational research in the future:

We’ll only do generational analysis when we have historical data that allows us to compare generations at similar stages of life. When comparing generations, it’s crucial to control for age. In other words, researchers need to look at each generation or age cohort at a similar point in the life cycle. (“Age cohort” is a fancy way of referring to a group of people who were born around the same time.)

When doing this kind of research, the question isn’t whether young adults today are different from middle-aged or older adults today. The question is whether young adults today are different from young adults at some specific point in the past.

To answer this question, it’s necessary to have data that’s been collected over a considerable amount of time – think decades. Standard surveys don’t allow for this type of analysis. We can look at differences across age groups, but we can’t compare age groups over time.

Another complication is that the surveys we conducted 20 or 30 years ago aren’t usually comparable enough to the surveys we’re doing today. Our earlier surveys were done over the phone, and we’ve since transitioned to our nationally representative online survey panel , the American Trends Panel . Our internal testing showed that on many topics, respondents answer questions differently depending on the way they’re being interviewed. So we can’t use most of our surveys from the late 1980s and early 2000s to compare Gen Z with Millennials and Gen Xers at a similar stage of life.

This means that most generational analysis we do will use datasets that have employed similar methodologies over a long period of time, such as surveys from the U.S. Census Bureau. A good example is our 2020 report on Millennial families , which used census data going back to the late 1960s. The report showed that Millennials are marrying and forming families at a much different pace than the generations that came before them.

Even when we have historical data, we will attempt to control for other factors beyond age in making generational comparisons. If we accept that there are real differences across generations, we’re basically saying that people who were born around the same time share certain attitudes or beliefs – and that their views have been influenced by external forces that uniquely shaped them during their formative years. Those forces may have been social changes, economic circumstances, technological advances or political movements.

When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

The tricky part is isolating those forces from events or circumstances that have affected all age groups, not just one generation. These are often called “period effects.” An example of a period effect is the Watergate scandal, which drove down trust in government among all age groups. Differences in trust across age groups in the wake of Watergate shouldn’t be attributed to the outsize impact that event had on one age group or another, because the change occurred across the board.

Changing demographics also may play a role in patterns that might at first seem like generational differences. We know that the United States has become more racially and ethnically diverse in recent decades, and that race and ethnicity are linked with certain key social and political views. When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

Controlling for these factors can involve complicated statistical analysis that helps determine whether the differences we see across age groups are indeed due to generation or not. This additional step adds rigor to the process. Unfortunately, it’s often absent from current discussions about Gen Z, Millennials and other generations.

When we can’t do generational analysis, we still see value in looking at differences by age and will do so where it makes sense. Age is one of the most common predictors of differences in attitudes and behaviors. And even if age gaps aren’t rooted in generational differences, they can still be illuminating. They help us understand how people across the age spectrum are responding to key trends, technological breakthroughs and historical events.

Each stage of life comes with a unique set of experiences. Young adults are often at the leading edge of changing attitudes on emerging social trends. Take views on same-sex marriage , for example, or attitudes about gender identity .

Many middle-aged adults, in turn, face the challenge of raising children while also providing care and support to their aging parents. And older adults have their own obstacles and opportunities. All of these stories – rooted in the life cycle, not in generations – are important and compelling, and we can tell them by analyzing our surveys at any given point in time.

When we do have the data to study groups of similarly aged people over time, we won’t always default to using the standard generational definitions and labels. While generational labels are simple and catchy, there are other ways to analyze age cohorts. For example, some observers have suggested grouping people by the decade in which they were born. This would create narrower cohorts in which the members may share more in common. People could also be grouped relative to their age during key historical events (such as the Great Recession or the COVID-19 pandemic) or technological innovations (like the invention of the iPhone).

By choosing not to use the standard generational labels when they’re not appropriate, we can avoid reinforcing harmful stereotypes or oversimplifying people’s complex lived experiences.

Existing generational definitions also may be too broad and arbitrary to capture differences that exist among narrower cohorts. A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations. The key is to pick a lens that’s most appropriate for the research question that’s being studied. If we’re looking at political views and how they’ve shifted over time, for example, we might group people together according to the first presidential election in which they were eligible to vote.

With these considerations in mind, our audiences should not expect to see a lot of new research coming out of Pew Research Center that uses the generational lens. We’ll only talk about generations when it adds value, advances important national debates and highlights meaningful societal trends.

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Kim Parker is director of social trends research at Pew Research Center

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Venus exploration remains key to understanding exo-earths, says paper.

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NEW YORK, NY - JUNE 5: In this handout image provided by NASA, Liz Heller and Andriel Mesznik watch ... [+] the transit of Venus on June 5, 2012 in New York, New York. The Transit of Venus involves the planet Venus crossing in front of the sun. The next pair of events will not happen again until the year 2117 and 2125. (Photo by Bill Ingalls/NASA via Getty Images)

To paraphrase Winston Churchill, our sister planet Venus remains a riddle, wrapped in a mystery, inside an enigma. Remarkably similar in size, mass, and bulk makeup, today, Earth and Venus couldn't be more different. Earth is an ecological utopia while Venus is a poster child for planetary desolation.

The conventional view is that Venus simply formed too close to our evolving yellow dwarf star to maintain liquid water at its surface. But in the last few decades, that view has come to be seen as simplistic. That’s because this explanation fails to adequately answer why Venus came to have surface temperatures hot enough to melt lead and atmospheric surface pressures ninety times that of Earth.

Even so, the authors of a new paper being published today in the journal Nature Astronomy argue that Venus remains crucial to understanding earth-mass and earth-like planets circling other stars.

Venus represents an astrobiological cautionary tale. That’s because observations of terrestrial mass exoplanets that —- at first glance —- would appear to be habitable may simply be producing an abundance of abiotic oxygen. That is, oxygen that has nothing to do with life on the planets’ surfaces.

Venus. The planet Venus, the second planet from the Sun, has the longest rotation period (243 days) ... [+] of any planet in the Solar System. It orbits the Sun every 224.7 Earth days, making a Venusian year shorter than an Earth year. Artist NASA. (Photo by Heritage Space/Heritage Images/Getty Images)

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In the late 1970s, NASA’s Pioneer Venus orbiter mission detected evidence for the catastrophic outgassing of an ocean’s worth of water. The abiotic oxygen produced during this outgassing would have been readily visible to alien astronomers if they were looking our way. We can only speculate whether some other intelligent civilization at the time might have misinterpreted our own Venus as being habitable due to this putative abundance of abiotic oxygen.

Such scenarios only illustrate how difficult it is going to be to say with any certainty that a given exoplanet may harbor life.

Venus As Research Lab

We are extremely lucky to have Venus right next door; it's likely the only other large rocky world we will ever get to, Paul Byrne, a planetary scientist at Washington University in St. Louis, and the paper’s co-author, told me via email. Earth-size worlds in other planetary systems are light years away; we have no foreseeable means of reaching them, says Byrne.

In order to really understand how you obtain conditions which are suitable for life to form in the first place, you really need to understand the past the present and future of planets and how they evolve with time, Stephen Kane, the paper’s lead author and a planetary astrophysicist at the University of California, Riverside, told me via phone. That's why we argue that Venus is really the key to that because it shows an extremely different evolution from Earth, he says.

In contrast to Earth, Venus has a rotational period of 243 days. Its atmosphere is almost entirely Carbon Dioxide CO2 (with a small amount of nitrogen and trace abundances of other gases) such as sulfur dioxide, argon and water vapor, the authors write. Moreover, the planet is cloaked in a global layer of sulfuric acid clouds, they note.

Byrne points out that although Venus and Earth formed in the same manner as the other rocky planets in our solar system, it’s still a puzzle as to why they took such divergent evolutionary paths.

If you move a planet too close to the star, then it's going to lose the primary atmosphere that it formed with and it's going to create a secondary atmosphere, says Kane. But if it's too close to the star, the planet will also lose its secondary atmosphere, he says.

Illustration of NASA's Pioneer Venus Orbiter mission.

Kane says that one of the most interesting things about Earth is that it has had surface liquid water for about 4 billion years. This means that Earth has had to maintain a very narrow temperature range, which he calls “extraordinary.”

As For A Solar System Without A Venus Analog?

If we did not have Venus, you can only imagine what we would be inferring about the Earth size planet population that we're currently discovering around other stars, says Kane. That’s because our models would never predict Venus, he says.

Earth and Venus are the same size and the same mass, but on a planetary scale everything else about Venus is different, says Kane. The magnetic field is different, the rotation rate is different, and Venus doesn't have a moon, so its axial tilt is different, he says.

Kane is also puzzled by Venus’ slow rotation rate and how it’s changed over time.

With Venus, we now think that the atmosphere itself has slowed the planet down, says Kane. It’s been assumed that Venus always was a slow rotator, but we don't know that, he says. And we don't fully understand the effect that the change in Venus' rotation rate has had on its climate evolution, says Kane.

Is there hope of ever understanding our sister planet?

For a start, a fleet of spacecraft will investigate Venus over the next decade, says the European Space Agency. They include ESA’s Envision mission, NASA’s VERITAS orbiter and DAVINCI probe, and India’s Shukrayaan orbiter.

These upcoming missions represent the best next step in making Venus a research priority.

As we discover more and more Earth- size worlds orbiting other stars we'll need to figure out how to distinguish those that are like Venus from those that are like Earth, says Byrne. If it's solely based on distance to the host star, then distinguishing that will be straightforward, he says. But if it's more complicated, and Earth-like worlds can form and be stable closer in to their parent stars, then we're going to have to understand why Venus and Earth turned out so differently, Byrne notes.

But Was Venus Ever Earth-Like?

Whether the answer is yes or no, figuring out this mystery is going to be a big deal, says Byrne.

And it will help us better understand our own planet.

Figuring out when, why, and how Venus ended up different to Earth will tell us how Earth has managed to stay habitable for almost its entire lifetime, says Byrne.

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Breaking news, yale professor accuses columbia prez shafik of plagiarism, ‘intellectual theft’ in resurfaced 1994 research paper.

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Embattled Columbia University president Nemat “Minouche” Shafik screwed a former underling out of credit on a research paper published 30 years ago, a Yale University professor claims.

Ahmed Mushfiq Mobarak posted the bombshell allegations in a blistering thread on X early Friday, juxtaposing images of a 1992 report Shafik co-authored for World Bank with researcher Sushenjit Bandyopadhyay, along with a journal published in Oxford Economic Papers two years later in which Bandyopadhyay’s name was removed.

Mobarak, an economics and management professor at Yale, told The Post the findings and research cited in both papers are pretty much equal.

“It got rewritten, but fundamentally it’s the same paper,” he alleged.

“We can’t get in the room and [learn] what sentences did he write and what sentences she wrote, but what we do know is his contribution was sufficient to warrant co-authorship [in 1992],” he added. “What is not common is for someone to be a co-author and then suddenly their name is taken off.”

Instead, Bandyopadhyay is only “thanked” in an acknowledgement section in the back of the 1994 published journal — which screams of “power asymmetry” considering Shafik was then Bandyopadhyay’s boss, alleged Mobarak.

Bandyopadhyay declined comment when asked whether he felt slighted.

However, Mobarak, also a former World Bank consultant and University of Maryland graduate, said he spoke to Bandyopadhyay about the issue and that Bandyopadhyay believes he should have been credited as a co-author in the second paper. The professor conceded Bandyopadhyay never said anything “negative” about the Columbia president.

“This [1994] paper is lifted almost entirely from a 1992 report coauthored with consultant not credited in the publication,” wrote Mobarak on X. “This is wholesale intellectual theft, not subtle plagiarism.”

At the time both papers were written, Shafik was a vice president for World Bank and Bandyopadhyay, a consultant who also attended the University of Maryland.

Mobarak’s allegations echo plagiarism accusations leveled against former Harvard University president Claudine Gay, who eventually resigned in disgrace in January .

Columbia University spokesperson Ben Chang shot down the Yale professor’s claims, saying “this is an absurd attempt at running a well-known playbook, and it has no credibility.”

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PENN GLOBAL RESEARCH & ENGAGEMENT GRANT PROGRAM 2024 Grant Program Awardees

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In 2024, Penn Global will support 24 new faculty-led research and engagement projects at a total funding level of $1.5 million.

The Penn Global Research and Engagement Grant Program prioritizes projects that bring together leading scholars and practitioners across the University community and beyond to develop new insight on significant global issues in key countries and regions around the world, a core pillar of Penn’s global strategic framework. 

PROJECTS SUPPORTED BY THE HOLMAN AFRICA RESEARCH AND ENGAGEMENT FUND

• Global Medical Physics Training & Development Program  Stephen Avery, Perelman School of Medicine
• Developing a Dakar Greenbelt with Blue-Green Wedges Proposal  Eugenie Birch, Weitzman School of Design
• Emergent Judaism in Sub-Saharan Africa  Peter Decherney, School of Arts and Sciences / Sara Byala, School of Arts and Sciences
• Determinants of Cognitive Aging among Older Individuals in Ghana  Irma Elo, School of Arts and Sciences
• Disrupted Aid, Displaced Lives Guy Grossman, School of Arts and Sciences
• A History of Regenerative Agriculture Practices from the Global South: Case Studies from Ethiopia, Kenya, and Zimbabwe Thabo Lenneiye, Kleinman Energy Center / Weitzman School of Design
• Penn Computerized Neurocognitive Battery Use in Botswana Public Schools Elizabeth Lowenthal, Perelman School of Medicine
• Podcasting South African Jazz Past and Present Carol Muller, School of Arts and Sciences
• Lake Victoria Megaregion Study: Joint Lakefront Initiative Frederick Steiner, Weitzman School of Design
• Leveraging an Open Source Software to Prevent and Contain AMR Jonathan Strysko, Perelman School of Medicine
• Poverty reduction and children's neurocognitive growth in Cote d'Ivoire Sharon Wolf, Graduate School of Education
• The Impacts of School Connectivity Efforts on Education Outcomes in Rwanda  Christopher Yoo, Carey Law School

PROJECTS SUPPORTED BY THE INDIA RESEARCH AND ENGAGEMENT FUND

• Routes Beyond Conflict: A New Approach to Cultural Encounters in South Asia  Daud Ali, School of Arts and Sciences
• Prioritizing Air Pollution in India’s Cities Tariq Thachil, Center for the Advanced Study of India / School of Arts and Sciences
• Intelligent Voicebots to Help Indian Students Learn English Lyle Ungar, School of Engineering and Applied Sciences

PROJECTS SUPPORTED BT THE CHINA RESEARCH AND ENGAGEMENT FUND

• Planning Driverless Cities in China Zhongjie Lin, Weitzman School of Design

PROJECTS SUPPORTED BY THE GLOBAL ENGAGEMENT FUND 

• Education and Economic Development in Nepal Amrit Thapa, Graduate School of Education
• Explaining Climate Change Regulation in Cities: Evidence from Urban Brazil Alice Xu, School of Arts and Sciences
• Nurse Staffing Legislation for Scotland: Lessons for the U.S. and the U.K.  Eileen Lake, School of Nursing
• Pathways to Education Development & Their Consequences: Finland, Korea, US Hyunjoon Park, School of Arts and Sciences
• Engaged Scholarship in Latin America: Bridging Knowledge and Action Tulia Falleti, School of Arts and Sciences
• Organizing Migrant Communities to Realize Rights in Palermo, Sicily  Domenic Vitiello, Weitzman School of Design
• Exploiting Cultural Heritage in 21st Century Conflict   Fiona Cunningham, School of Arts and Sciences
• Center for Integrative Global Oral Health   Alonso Carrasco-Labra, School of Dental Medicine

This first-of-its-kind Global Medical Physics Training and Development Program (GMPTDP) seeks to serve as an opportunity for PSOM and SEAS graduate students to enhance their clinical requirement with a global experience, introduce them to global career opportunities and working effectively in different contexts, and strengthens partnerships for education and research between US and Africa. This would also be an exceptional opportunity for pre-med/pre-health students and students interested in health tech to have a hands-on global experience with some of the leading professionals in the field. The project will include instruction in automated radiation planning through artificial intelligence (AI); this will increase access to quality cancer care by standardizing radiation planning to reduce inter-user variability and error, decreasing workload on the limited radiation workforce, and shortening time to treatment for patients. GMPTDP will offer a summer clinical practicum to Penn students during which time they will also collaborate with UGhana to implement and evaluate AI tools in the clinical workflow.

The proposal will address today’s pressing crises of climate change, land degradation, biodiversity loss, and growing economic disparities with a holistic approach that combines regional and small-scale actions necessary to achieve sustainability. It will also tackle a key issue found across sub-Saharan Africa, many emerging economies, and economically developed countries that struggle to control rapid unplanned urbanization that vastly outpaces the carrying capacity of the surrounding environment.

The regional portion of the project will create a framework for a greenbelt that halts the expansion of the metropolitan footprint. It will also protect the Niayes, an arable strip of land that produces over 80% of the country’s vegetables, from degradation. This partnership will also form a south-south collaboration to provide insights into best practices from a city experiencing similar pressures.

The small-scale portion of the project will bolster and create synergy with ongoing governmental and grassroots initiatives aimed at restoring green spaces currently being infilled or degraded in the capital. This will help to identify overlapping goals between endeavors, leading to collaboration and mobilizing greater funding possibilities instead of competing over the same limited resources. With these partners, we will identify and design Nature-based Solutions for future implementation.

Conduct research through fieldwork to examine questions surrounding Jewish identity in Africa. Research will be presented in e.g. articles, photographic images, and films, as well as in a capstone book. In repeat site-visits to Uganda, South Africa, Ghana, and Zimbabwe, we will conduct interviews with and take photographs of stakeholders from key communities in order to document their everyday lives and religious practices.

The overall aim of this project is the development of a nationally representative study on aging in Ghana. This goal requires expanding our network of Ghanian collaborators and actively engage them in research on aging. The PIs will build on existing institutional contacts in Ghana that include:

1). Current collaboration with the Navrongo Health Research Center (NCHR) on a pilot data collection on cognitive aging in Ghana (funded by a NIA supplement and which provides the matching funds for this Global Engagement fund grant application);

2) Active collaboration with the Regional Institute for Population Studies (RIPS), University of Ghana. Elo has had a long-term collaboration with Dr. Ayaga Bawah who is the current director of RIPS.

In collaboration with UNHCR, we propose studying the effects of a dramatic drop in the level of support for refugees, using a regression discontinuity design to survey 2,500 refugee households just above and 2,500 households just below the vulnerability score cutoff that determines eligibility for full rations. This study will identify the effects of aid cuts on the welfare of an important marginalized population, and on their livelihood adaptation strategies. As UNHCR faces budgetary cuts in multiple refugee-hosting contexts, our study will inform policymakers on the effects of funding withdrawal as well as contribute to the literature on cash transfers.

The proposed project, titled "A History of Regenerative Agriculture Practices from the Global South: Case Studies from Ethiopia, Kenya, and Zimbabwe," aims to delve into the historical and contemporary practices of regenerative agriculture in sub-Saharan Africa. Anticipated Outputs and Outcomes:

1. Research Paper: The primary output of this project will be a comprehensive research paper. This paper will draw from a rich pool of historical and contemporary data to explore the history of regenerative agriculture practices in Ethiopia, Kenya, and Zimbabwe. It will document the indigenous knowledge and practices that have sustained these regions for generations.

2. Policy Digest: In addition to academic research, the project will produce a policy digest. This digest will distill the research findings into actionable insights for policymakers, both at the national and international levels. It will highlight the benefits of regenerative agriculture and provide recommendations for policy frameworks that encourage its adoption.

3. Long-term Partnerships: The project intends to establish long-term partnerships with local and regional universities, such as Great Lakes University Kisumu, Kenya. These partnerships will facilitate knowledge exchange, collaborative research, and capacity building in regenerative agriculture practices. Such collaborations align with Penn Global's goal of strengthening institutional relationships with African partners.

The Penn Computerized Neurocognitive Battery (PCNB) was developed at the University of Pennsylvania by Dr. Ruben C. Gur and colleagues to be administered as part of a comprehensive neuropsychiatric assessment. Consisting of a series of cognitive tasks that help identify individuals’ cognitive strengths and weaknesses, it has recently been culturally adapted and validated by our team for assessment of school-aged children in Botswana . The project involves partnership with the Botswana Ministry of Education and Skills Development (MoESD) to support the rollout of the PCNB for assessment of public primary and secondary school students in Botswana. The multidisciplinary Penn-based team will work with partners in Botswana to guide the PCNB rollout, evaluate fidelity to the testing standards, and track student progress after assessment and intervention. The proposed project will strengthen a well-established partnership between Drs. Elizabeth Lowenthal and J. Cobb Scott from the PSOM and in-country partners. Dr. Sharon Wolf, from Penn’s Graduate School of Education, is an expert in child development who has done extensive work with the Ministry of Education in Ghana to support improvements in early childhood education programs. She is joining the team to provide the necessary interdisciplinary perspective to help guide interventions and evaluations accompanying this new use of the PCNB to support this key program in Africa.

This project will build on exploratory research completed by December 24, 2023 in which the PI interviewed about 35 South Africans involved in jazz/improvised music mostly in Cape Town: venue owners, curators, creators, improvisers.

• Podcast series with 75-100 South African musicians interviewed with their music interspersed in the program.
• 59 minute radio program with extended excerpts of music inserted into the interview itself.
• Create a center of knowledge about South African jazz—its sound and its stories—building knowledge globally about this significant diasporic jazz community
• Expand understanding of “jazz” into a more diffuse area of improvised music making that includes a wide range of contemporary indigenous music and art making
• Partner w Lincoln Center Jazz (and South African Tourism) to host South Africans at Penn

This study focuses on the potential of a Megaregional approach for fostering sustainable development, economic growth, and social inclusion within the East African Community (EAC), with a specific focus on supporting the development of A Vision for An Inclusive Joint Lakefront across the 5 riparian counties in Kenya.

By leveraging the principles of Megaregion development, this project aims to create a unified socio-economic, planning, urbanism, cultural, and preservation strategy that transcends county boundaries and promotes collaboration further afield, among the EAC member countries surrounding the Lake Victoria Basin.

Anticipated Outputs and Outcomes:

1. Megaregion Conceptual Framework: The project will develop a comprehensive Megaregion Conceptual Framework for the Joint Lakefront region in East Africa. This framework, which different regions around the world have applied as a way of bridging local boundaries toward a unified regional vision will give the Kisumu Lake region a path toward cooperative, multi-jurisdictional planning. The Conceptual Framework will be both broad and specific, including actionable strategies, projects, and initiatives aimed at sustainable development, economic growth, social inclusion, and environmental stewardship.

2. Urbanism Projects: Specific urbanism projects will be proposed for key urban centers within the Kenyan riparian counties. These projects will serve as tangible examples of potential improvements and catalysts for broader development efforts.

3. Research Publication: The findings of the study will be captured in a research publication, contributing to academic discourse and increasing Penn's visibility in the field of African urbanism and sustainable development

Antimicrobial resistance (AMR) has emerged as a global crisis, causing more deaths than HIV/AIDS and malaria worldwide. By engaging in a collaborative effort with the Botswana Ministry of Health’s data scientists and experts in microbiology, human and veterinary medicine, and bioinformatics, we will aim to design new electronic medical record system modules that will:

Aim 1: Support the capturing, reporting, and submission of microbiology data from sentinel surveillance laboratories as well as pharmacies across the country

Aim 2: Develop data analytic dashboards for visualizing and characterizing regional AMR and AMC patterns

Aim 3: Submit AMR and AMC data to regional and global surveillance programs

Aim 4: Establish thresholds for alert notifications when disease activity exceeds expected incidence to serve as an early warning system for outbreak detection.

  Using a novel interdisciplinary approach that bridges development economics, psychology, and neuroscience, the overall goal of this project is to improve children's development using a poverty-reduction intervention in Cote d'Ivoire (CIV). The project will directly measure the impacts of cash transfers (CTs) on neurocognitive development, providing a greater understanding of how economic interventions can support the eradication of poverty and ensure that all children flourish and realize their full potential. The project will examine causal mechanisms by which CTs support children’s healthy neurocognitive development and learning outcomes through the novel use of an advanced neuroimaging tool, functional Near Infrared Spectroscopy (fNIRS), direct child assessments, and parent interviews.

The proposed research, the GIGA initiative for Improving Education in Rwanda (GIER), will produce empirical evidence on the impact of connecting schools on education outcomes to enable Rwanda to better understand how to accelerate the efforts to bring connectivity to schools, how to improve instruction and learning among both teachers and students, and whether schools can become internet hubs capable of providing access e-commerce and e-government services to surrounding communities. In addition to evaluating the impact of connecting schools on educational outcomes, the research would also help determine which aspects of the program are critical to success before it is rolled out nationwide.

Through historical epigraphic research, the project will test the hypothesis that historical processes and outcomes in the 14th century were precipitated by a series of related global and local factors and that, moreover, an interdisciplinary and synergistic analysis of these factors embracing climatology, hydrology, epidemiology linguistics and migration will explain the transformation of the cultural, religious and social landscapes of the time more effectively than the ‘clash of civilizations’ paradigm dominant in the field. Outputs include a public online interface for the epigraphic archive; a major international conference at Penn with colleagues from partner universities (Ghent, Pisa, Edinburgh and Penn) as well as the wider South Asia community; development of a graduate course around the research project, on multi-disciplinary approaches to the problem of Hindu-Muslim interaction in medieval India; and a public facing presentation of our findings and methods to demonstrate the path forward for Indian history. Several Penn students, including a postdoc, will be actively engaged.  

India’s competitive electoral arena has failed to generate democratic accountability pressures to reduce toxic air. This project seeks to broadly understand barriers to such pressures from developing, and how to overcome them. In doing so, the project will provide the first systematic study of attitudes and behaviors of citizens and elected officials regarding air pollution in India. The project will 1) conduct in-depth interviews with elected local officials in Delhi, and a large-scale survey of elected officials in seven Indian states affected by air pollution, and 2) partner with relevant civil society organizations, international bodies like the United Nations Environment Program (UNEP), domain experts at research centers like the Public Health Foundation of India (PHFI), and local civic organizations (Janagraaha) to evaluate a range of potential strategies to address pollution apathy, including public information campaigns with highly affected citizens (PHFI), and local pollution reports for policymakers (Janagraaha).

The biggest benefit from generative AI such as GPT, will be the widespread availability of tutoring systems to support education. The project will use this technology to build a conversational voicebot to support Indian students in learning English. The project will engage end users (Indian tutors and their students) in the project from the beginning. The initial prototype voice-driven conversational system will be field-tested in Indian schools and adapted. The project includes 3 stages of development:

1) Develop our conversational agent. Specify the exact initial use case and Conduct preliminary user testing.

2) Fully localize to India, addressing issues identified in Phase 1 user testing.

3) Do comprehensive user testing with detailed observation of 8-12 students using the agent for multiple months; conduct additional assessments of other stakeholders.

The project partners with Ashoka University and Pratham over all three stages, including writing scholarly papers.

Through empirical policy analysis and data-based scenario planning, this project actively contributes to this global effort by investigating planning and policy responses to autonomous transportation in the US and China. In addition to publishing several research papers on this subject, the PI plans to develop a new course and organize a forum at PWCC in 2025. These initiatives are aligned with an overarching endeavor that the PI leads at the Weitzman School of Design, which aims to establish a Future Cities Lab dedicated to research and collaboration in the pursuit of sustainable cities.

This study aims to fill this gap through a more humanistic approach to measuring the impact of education on national development. Leveraging a mixed methods research design consisting of analysis of quantitative data for trends over time, observations of schools and classrooms, and qualitative inquiry via talking to people and hearing their stories, we hope to build a comprehensive picture of educational trends in Nepal and their association with intra-country development. Through this project we strive to better inform the efforts of state authorities and international organizations working to enhance sustainable development within Nepal, while concurrently creating space and guidance for further impact analyses. Among various methods of dissemination of the study’s findings, one key goal is to feed this information into writing a book on this topic.

Developing cities across the world have taken the lead in adopting local environmental regulation. Yet standard models of environmental governance begin with the assumption that local actors should have no incentives for protecting “the commons.” Given the benefits of climate change regulation are diffuse, individual local actors face a collective action problem. This project explores why some local governments bear the costs of environmental regulation while most choose to free-ride. The anticipated outputs of the project include qualitative data that illuminate case studies and the coding of quantitative spatial data sets for studying urban land-use. These different forms of data collection will allow me to develop and test a theoretical framework for understanding when and why city governments adopt environmental policy.

The proposed project will develop new insights on the issue of legislative solutions to the nurse staffing crisis, which will pertain to many U.S. states and U.K. countries. The PI will supervise the nurse survey data collection and to meet with government and nursing association stakeholders to plan the optimal preparation of reports and dissemination of results. The anticipated outputs of the project are a description of variation throughout Scotland in hospital nursing features, including nurse staffing, nurse work environments, extent of adherence to the Law’s required principles, duties, and method, and nurse intent to leave. The outcomes will be the development of capacity for sophisticated quantitative research by Scottish investigators, where such skills are greatly needed but lacking.  

The proposed project will engage multi-cohort, cross-national comparisons of educational-attainment and labor-market experiences of young adults in three countries that dramatically diverge in how they have developed college education over the last three decades: Finland, South Korea and the US. It will produce comparative knowledge regarding consequences of different pathways to higher education, which has significant policy implications for educational and economic inequality in Finland, Korea, the US, and beyond. The project also will lay the foundation for ongoing collaboration among the three country teams to seek external funding for sustained collaboration on educational analyses.

With matching funds from PLAC and CLALS, we will jointly fund four scholars from diverse LAC countries to participate in workshops to engage our community regarding successful practices of community-academic partnerships.

These four scholars and practitioners from Latin America, who are experts on community-engaged scholarship, will visit the Penn campus during the early fall of 2024. As part of their various engagements on campus, these scholars will participate after the workshops as key guest speakers in the 7th edition of the Penn in Latin America and the Caribbean (PLAC) Conference, held on October 11, 2024, at the Perry World House. The conference will focus on "Public and Community Engaged Scholarship in Latin America, the Caribbean, and their Diasporas."

Palermo, Sicily, has been a leading center of migrant rights advocacy and migrant civic participation in the twenty-first century. This project will engage an existing network of diverse migrant community associations and anti-mafia organizations in Palermo to take stock of migrant rights and support systems in the city. Our partner organizations, research assistants, and cultural mediators from different communities will design and conduct a survey and interviews documenting experiences, issues and opportunities related to various rights – to asylum, housing, work, health care, food, education, and more. Our web-based report will include recommendations for city and regional authorities and other actors in civil society. The last phase of our project will involve community outreach and organizing to advance these objectives. The web site we create will be designed as the network’s information center, with a directory of civil society and services, updating an inventory not current since 2014, which our partner Diaspore per la Pace will continue to update.

This interdisciplinary project has four objectives: 1) to investigate why some governments and non-state actors elevated cultural heritage exploitation (CHX) to the strategic level of warfare alongside nuclear weapons, cyberattacks, political influence operations and other “game changers”; 2) which state or non-state actors (e.g. weak actors) use heritage for leverage in conflict and why; and 3) to identify the mechanisms through which CHX coerces an adversary (e.g. catalyzing international involvement); and 4) to identify the best policy responses for non-state actors and states to address the challenge of CHX posed by their adversaries, based on the findings produced by the first three objectives.

Identify the capacity of dental schools, organizations training oral health professionals and conducting oral health research to contribute to oral health policies in the WHO Eastern Mediterranean region, identify the barriers and facilitators to engage in OHPs, and subsequently define research priority areas for the region in collaboration with the WHO, oral health academia, researchers, and other regional stakeholders.

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