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.
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.