Impact of Social Media Use on the Life Satisfaction of Adolescents in South Korea Through Social Support and Social Capital

Abstract

This study investigated how social media use among South Korean adolescents influences life satisfaction, using two-wave panel survey data. Specifically, this study examined the mediating mechanism by which adolescents’ social media use is associated with their life satisfaction through social support and social capital. The results demonstrated that social support and social capital mediate the relationship between social media use and life satisfaction. Social media use is positively related to social support, and social support has a positive relationship with a higher level of social capital which, in turn, is related to a higher level of life satisfaction. This study improves our understanding of the relationship between social media use and adolescents’ life satisfaction and presents significant implications for those attempting to help such individuals promote their life satisfaction and mental health.

Keywords

adolescents life satisfaction social capital social media social support

Over the past decade, social media such as Facebook, Twitter, and Instagram have grown in popularity (Chai et al., 2019), and a large proportion of adolescents have spent time using social media (Twenge & Campbell, 2018). For instance, a nationwide survey in South Korea demonstrated that more than 80% of the country’s adolescents stated that they use social media (Korea Press Foundation, 2019). With the increasing popularity of social media, scholars have investigated how social media use influences psychological health, such as life satisfaction, particularly among adolescents (e.g., Keresteš & Štulhofer, 2020; Schemer et al., 2021).

Since social media represents a convenient and low-cost tool for promoting social interaction as it allows the sending and receiving of personalized messages using texts, images, voices, or videos (Choi & Noh, 2020a), social media use has the potential to influence the life satisfaction of adolescents. Life satisfaction refers to one’s subjective cognitive and affective evaluations of one’s overall quality of life in either a negative or positive direction (Choi & Noh, 2020a; Diener et al., 2002). It remains relatively stable over time, and is strongly related to psychological health outcomes, such as depression and anxiety (Levin et al., 2012). Life satisfaction can help adolescents acquire optimal psychological experiences and functioning (Bruggeman et al., 2019). Life satisfaction serves as a psychological resource that assists adolescents in handling difficulties, risks, and challenges (Antaramian et al., 2008; Geraee et al., 2019). Thus, it is important to explore how social media promote life satisfaction among adolescents.

Previous studies have demonstrated that adolescents’ social media use impacts their life satisfaction (e.g., Bruggeman et al., 2019; Dhir et al., 2017; Frison & Eggermont, 2016). Some scholars have argued that social media use is negatively associated with adolescents’ life satisfaction (e.g., de Lenne et al., 2020; Twenge & Campbell, 2018). However, other studies have demonstrated that social media use can positively affect life satisfaction (e.g., Valkenburg & Peter, 2007; Ziv & Kiasi, 2016). Extant studies have explored the relationship between these two factors and suggested various explanations. According to the social displacement hypothesis, adolescents who spend more time on social media have fewer opportunities to engage in face-to-face interactions, which may decrease their life satisfaction (Hall et al., 2019).

The literature also identified social support and social capital as important explanatory factors in the relationship between social media and life satisfaction. As adolescents’ life satisfaction is largely influenced by social factors (Kapikiran, 2013; Kong et al., 2012; Pang, 2018), further research is required to understand the dynamic mechanism underlying the relationship between the two aspects. While previous studies examined the individual relationships between social media use, social capital, social support, and life satisfaction (e.g., Drouin et al., 2018; S. Lee et al., 2018; Su & Chan, 2017), the current study explores the integrated and systematic indirect relationships among these variables. Specifically, this study contributes to the current literature by accounting for the serial mediating role of social support and social capital as social factors in exploring the association between social media use and life satisfaction. Moreover, there has been little research on the sequential associations between social media use, social support, social capital, and life satisfaction among South Korean adolescents. Thus, this study provides valuable practical insights for improving mental health and life satisfaction among South Korean adolescents.

This study uses data from a two-wave panel survey conducted in 2017 and 2018 among South Korean adolescents to explore the mediating mechanisms of how social media use is related to life satisfaction through social support and social capital. While social support refers to the exchange of psychological assets, such as verbal or nonverbal messages, information, or emotions, through social interactions among significant individuals (Lin, 2011), social capital indicates the reciprocity and trust that enable cooperation among individuals to pursue shared goals through social relationships (Choi & Shin, 2017). The findings of this study will provide a better understanding of the relationship between social media use and life satisfaction among adolescents, and provide direction on how they can obtain benefits from social media use.

Conceptual Framework

Social Media Use and Life Satisfaction

The existing literature takes different sides when explaining the relationship between social media use and life satisfaction. One side suggests that social media use can facilitate life satisfaction by enhancing social ties and making social connections (Schemer et al., 2021). Moreover, social media use helps increase social capital, which in turn improves life satisfaction (Ellison et al., 2011). For example, a German longitudinal survey found that social media use for communication positively impacts life satisfaction (Dienlin et al., 2017). However, according to the other side, social media use decreases life satisfaction by inducing upward social comparison and envy (Schemer et al., 2021). Furthermore, adolescents’ use of social media can lead to encounters with distressing online experiences, such as cyberbullying, which is likely to negatively influence life satisfaction (Keresteš & Štulhofer, 2020). For instance, a panel data survey in Finland found that social media use negatively affects life satisfaction through loneliness (Marttila et al., 2021). Despite these mixed results, this study focuses on the role of social relationships derived from social media and their effects on life satisfaction.

As scholars have increasingly focused on the significance of life satisfaction (Geraee et al., 2019), they have sought to identify its determinants. Life satisfaction is known to be affected by social relationships (Kahneman & Krueger, 2006; Valenzuela et al., 2009). Social interactions and communication with others can play key roles in increasing life satisfaction (Dhir et al., 2017; B. Kim & Kim, 2017). Individuals with strong social connections and friends are more likely to be satisfied with their lives than those without such social relationships (Bruggeman et al., 2019). In particular, the creation and maintenance of social relationships is an important developmental process for adolescents and can be strongly related to life satisfaction (Best et al., 2014).

Moreover, in recent years, the development of communications technology has helped individuals to connect conveniently with others (Ellison et al., 2011). Social media such as Facebook, Twitter, and Instagram are designed to assist users in building and maintaining interpersonal relationships in online environments (Choi & Shin, 2017). Social media enable users to communicate and interact with other users efficiently and inexpensively using various multimedia tools on online networks, which can facilitate social relationships (Choi & Noh, 2020b). Notably, media use can promote life satisfaction as an increasing number of adolescents and youths use social media to connect and interact with others, such as friends or new acquaintances with similar or diverse interests (Bruggeman et al., 2019; Pew Research Center, 2018; Weinstein, 2018), Thus, it is plausible that social media use is positively associated with life satisfaction among adolescents. This leads to the following hypothesis.

H1: Social media use is positively associated with life satisfaction.

Mediating Effect of Social Support

As the exchange of social support is a key function of an individual’s social network (Lu & Hampton, 2017), this study suggests that social media use has a positive relationship with social support, which may be associated with life satisfaction. Social support can be defined as the exchange of psychological assets (such as information, emotions, appraisals, values, or behaviors) with others, or the supply of such assets by important others from the social network to which an individual belongs (Choi & Noh, 2020a; Kapikiran, 2013). People expect support from others with whom they have relational ties (Cheng, 1998). Social support in the form of advice or emotional comfort can help individuals negotiate difficult situations (Li & Peng, 2019). In particular, social support and supportive relationships are very important for improved adolescent development (Urberg et al., 2005). For example, social support can help students and adolescents adjust to their school lives (Drouin et al., 2018). Furthermore, social support has been found to influence life satisfaction (e.g., Kong et al., 2012; Park et al., 2012). There are several explanations for the positive relationship between social support and life satisfaction. Social support from other people can play a significant role in the promotion of life satisfaction, as it can contribute to the reduction of social isolation and meet a person’s need for interpersonal interaction (Başol, 2008; Gibson & Trnka, 2020). Social relationships significantly affect people’s lives.

Moreover, social support can offer individuals a sense of belonging and connectedness, which can increase life satisfaction (Oh et al., 2014). Social support can also boost self-esteem by offering encouragement and positive feedback, which in turn improves life satisfaction (Danielsen et al., 2009). social support can positively influence life satisfaction by attenuating the negative effects of stressful situations (Shen & Yeatts, 2013). Empirical survey research in China demonstrated that social support has a positive relationship with life satisfaction (W. Chen et al., 2017). Thus, social support among adolescents is likely to be positively related to life satisfaction.

Furthermore, as social support involves social interaction, it can be facilitated through social media use (Choi & Noh, 2020a; Yen, 2016). As social media allow the efficient exchange of emotional and informational resources among users, it offers opportunities to connect and receive social support from other people through online networks (Shensa et al., 2020). Popular activities on social media, such as commenting on other users’ posts and sending private messages, present opportunities (or affordances) to offer social support (Lu & Hampton, 2017). For example, paralinguistic digital affordance on social media—which refers to cues or tools such as the “like” function on Facebook, Instagram, or Twitter that enable interaction and communication among users without using language or verbal messages—plays an important role in promoting social support (Wohn et al., 2016). Further, social media allow users to self-disclose when they need social support (Quan-Haase et al., 2017).

For adolescents, social media can foster exchanges of social support due to the constant availability of friends or family members online, at any time and in any location (Hatchel et al., 2019). For example, adolescents use social media to openly share their experiences with peers and friends, and to offer social support because they prefer to confide in them rather than in adults (Gibson & Trnka, 2020). Prior research has demonstrated that social media use is positively associated with social support (Drouin et al., 2018; Lönnqvist & große Deters, 2016). Thus, social media use is likely to have a positive effect on social support.

Based on existing findings on the effects of social media use and social support on life satisfaction, this study suggests that social support mediates the association between social media use and life satisfaction. Social media use among adolescents may facilitate social support, which can promote their life satisfaction. This leads to the following hypothesis.

H2: Social support mediates the relationship between social media use and life satisfaction.

Mediating Effect of Social Capital

One of the major benefits of social media is that it can facilitate the provision of social capital, an essential aspect of adolescents’ social lives (Antheunis et al., 2016; Cheng et al., 2019). Social capital refers to the resources that individuals derive from social interactions within their social networks (Coleman, 1988; Ellison et al., 2011). These resources include reciprocity and trust, which allow people to cooperate and pursue mutual benefits and shared goals through social relationships (Choi & Noh, 2020b; Putnam, 2000). Social capital can play a significant role in increasing individuals’ sense of social connectedness to their contacts and society (Phua et al., 2017), which can reduce social isolation and loneliness, and thereby improve their quality of life. Social connectedness also offers opportunities for social interaction and produces a pleasurable experience, which contributes to life satisfaction (Arampatzi et al., 2018). Moreover, social capital affected by one’s social network helps people access various beneficial opportunities, such as employment openings and educational resources (Valenzuela et al., 2009), which can increase life satisfaction. Social capital plays a significant role in promoting life satisfaction by fostering social relationships, trust, and resources among people. For adolescents, social capital becomes an important element as their social lives mature (Antheunis et al., 2016). Social capital helps adolescents build healthy and beneficial interpersonal relationships during their transition into adulthood, which can enhance their mental health and life satisfaction (Allan & Catts, 2014; J. Y. Lee et al., 2016). Empirical studies have found that social capital is strongly associated with life satisfaction (e.g., Arampatzi et al., 2018; B. J. Kim et al., 2015; S. Lee et al., 2018). Thus, social capital is likely to positively affect adolescents’ life satisfaction.

Moreover, because social capital is influenced by social relationships, social media use may play a significant role in increasing social capital (H. T. Chen & Li, 2017; Choi & Noh, 2020b). For example, social media users build their own webpages where they disclose personal information such as their name, age, hometown, and hobbies, and exchange personalized messages with others through chats, direct messages, wall posts, and status updates, all of which can increase interpersonal trust (Zhong, 2014). Social media also provide virtual spaces where people can join groups, communities, and fan pages, or play social games together (Abbas & Mesch, 2018; Ellison et al., 2011). By participating in diverse online activities and communicating with other networked contacts, social media users can build cooperative relationships that may elevate their social capital (Choi & Noh, 2020b). For adolescents, social media can sustain or reinforce existing social connections with family members or friends, new social relationships with other people, and access to social resources through online social networks (Abbas & Mesch, 2018; Manago & Melton, 2020). Previous studies have demonstrated that social media use is positively related to social capital (e.g., Ahn, 2012; Antheunis et al., 2016; Su & Chan, 2017; J. R. Williams, 2019). Therefore, it is likely that social media use among adolescents contributes to the promotion of social capital.

Based on the above discussion of the effect of social media use and social capital on life satisfaction, this study argues that social capital mediates the relationship between social media use and life satisfaction. Social media use among adolescents is positively related to social capital, which can, in turn, give them a higher level of life satisfaction. This leads to the following hypothesis.

H3: Social capital mediates the relationship between social media use and life satisfaction.

Finally, this study explores the mediating mechanisms through which social media use among adolescents is related to their life satisfaction through social support and social capital. As discussed previously, the use of social media can facilitate social support. Because social support provides guidance, information, assistance, or encouragement to others, it helps build social relationships and interactions and facilitates trust (Colvin et al., 2002; Oh et al., 2014), which is a key component of social capital. Moreover, social support can intensify reciprocity (Lin, 2011), an important element of social capital. When people receive social support, they may have an obligation to reciprocate that support to others (Lin, 2011). Reciprocity may also contribute to social capital formation. Social support plays a significant role in the formation and maintenance of social capital. Furthermore, since previous studies have demonstrated that social support can positively affect social capital (e.g., Lin, 2011; Primack et al., 2014; Zhou, 2016), this study hypothesizes that social support is positively associated with social capital, and may, in turn, lead to greater life satisfaction. Therefore, this study uses a multiple-mediator model to examine how social media use indirectly influences life satisfaction through social support and social capital.

H4: Social support mediates the association between social media use and social capital, which, in turn, mediates the relationship between social support and life satisfaction.

Figure 1 illustrates the proposed research model, indicating the associations between social media use, social support, social capital, and life satisfaction.

Figure 1.

Proposed research model.

Methods

Data

This study used panel survey data from the Korean Game Panel Study (KGPS). The KGPS is administered by the Korea Creative Content Agency, a South Korean government agency that coordinates the promotion of the Korean content industry, which includes games, broadcasting, and digital content. Panel survey data were collected from adolescents living in Seoul Metropolitan Area. These adolescents were recruited using a quota sampling method that considered the ratios of gender and their level in school. Face-to-face interviews were also conducted by trained interviewers. The same participants were interviewed each time and re-contacted by a professional research company in South Korea. The participants numbered 999 in 2017 (Time 1 or T1) and 801 in 2018 (Time 2 or T2). Thus, a final sample size of 801 was used for the analyses. The current study used two time periods because the survey participants were middle school and college freshmen, representing the adolescent transition to adulthood. There were 411 female participants (51.3%) and 390 male participants (48.7%). In terms of school level (or school class), there were 287 middle school participants (35.8%), 295 high school participants (36.8%), and 219 college freshmen or equivalent participants (27.3%). All participants were incentivized through vouchers (valued at approximately USD 50) to participate in the survey. The KGPS dataset has been publicly available since July 2019, and can be downloaded from the KGPS website.

Measures

Life Satisfaction

Life satisfaction was measured by asking participants to report the degree to which they agree with the following statements: “In most ways my life is close to my ideal,”“The conditions of my life are excellent,” and “I am satisfied with my life.” Answers were scored on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”). These 3 items were averaged to create an index of life satisfaction (Cronbach’s alpha = .91, M = 4.45, SD = 1.31). These items were adopted from previous research (Diener et al., 1985).

Social Media Use

Social media use was measured by considering the participants’ responses to a single question about how frequently they had used social media such as Facebook or Cyworld during the past 3 months. Answers were based on a six-point scale (1 = “not at all,” 6 = “very frequently”; M = 3.19, SD = 1.92). This measurement item was adopted from previous studies (Choi & Noh, 2020a; B. Kim & Kim, 2017; Yoo, 2019).

Social Support

Social support was measured by asking the participants to report, using a four-point scale (1 = “not at all,” 4 = “always”), the extent to which they agree with the following statements: “My friends comfort me when I am sad,”“My friends praise me when I perform well,” and “My friends support my strengths.” Responses to these 3 items were averaged together to construct an index of social support (Cronbach’s alpha = .90, M = 3.21, SD = 0.57). These measurement items were adopted from prior research (J. L. Lee, 1994).

Social Capital

Social capital was measured by asking the participants to report, using a 5-point scale (1 = “strongly disagree,” 5 = “strongly agree”), the degree to which they agree with the following six statements: “Interacting with people makes me interested in things that happen outside of my community,”“Interacting with people makes me want to try new things,”“Interacting with people connects me to the wider world,”“There are several people I trust to help solve my problems,”“There is someone I can turn to for advice regarding making very important decisions,” and “When I feel lonely, there are several people I can talk to.” Responses were averaged together to create an index of social capital (Cronbach’s alpha = .89, M = 3.87, SD = 0.63). The measurement items were adopted from earlier research (D. Williams, 2006).

Table 1 presents the results of the correlation analyses.

Table 1.

A Correlation Table.

Variables	1	2	3	4	5	6
1. Social media use	—
2. Social support	.11**	—
3. Social capital	.07*	.61***	—
4. Life satisfaction	.04	.42***	.47***	—
5. School class	.03	.04	−.05	−.20***	—
6. Gender	−.03	.05	−.01	−.09**	.04	—

p < .05. **p < .01. ***p < .001.

Validity

This study estimated the convergent validity of the three measurement variables (i.e., life satisfaction, social support, and social capital) using average variance extracted (AVE) values and factor loading scores (Fornell & Larcker, 1981; Hair et al., 2010). As indicated in Table 2, the factor loading scores for all 3 variable items were higher than 0.50, which is the cutoff criterion (Hair et al., 2010). The AVE values for all 3 variables were also higher than 0.50, which is the cutoff point (Fornell & Larcker, 1981). Thus, this study confirmed the convergent validity of the measurement items for each variable.

Table 2.

Convergent Validity.

Variables and items	Factor loading	Average variance extracted (AVE)
Life satisfaction		0.79
Item 1	0.91
Item 2	0.88
Item 3	0.87
Social support		0.77
Item 1	0.90
Item 2	0.88
Item 3	0.83
Social capital		0.58
Item 1	0.84
Item 2	0.83
Item 3	0.81
Item 4	0.73
Item 5	0.68
Item 6	0.64

Discriminant validity was estimated by comparing the AVE values of each variable with the shared variance between the variables (Fornell & Larcker, 1981). As indicated in Table 3, discriminant validity for all three variables was achieved, as the AVE values for each variable (bold in the table) were greater than the squared correlations between that variable and any others (Spreng et al., 1996).

Table 3.

Discriminant Validity.

Variable	1	2	3
1. Social support	0.77
2. Social capital	0.37	0.58
3. Life satisfaction	0.18	0.22	0.79

Note. Values in bold are the square roots of the average variance extracted between the constructs and their measurements (Noh et al., 2016).

Analysis

To examine the proposed hypotheses, this study used the SPSS PROCESS macro (Hayes, 2018, Model 6), through which ordinary least squares regression was employed to estimate both the direct and indirect effects of social media use (T1) on life satisfaction (T2). Specifically, after controlling for gender (T1) and school class (T1), a simultaneous test was conducted regarding the impact of social media use (T1) on two serial mediators (social support at T2 and social capital at T2) and their subsequent effects on life satisfaction (T2). Using life satisfaction at T2 as the outcome and life satisfaction at T1 as the covariate, this study assessed the effect of social media use as it changed over time. In particular, when assessing indirect effects, the 95% bias-corrected bootstrap method was used with 5,000 bootstrap samples, which produced more accurate confidence intervals (Hayes, 2018). In the bootstrapping analysis, indirect effects were considered statistically significant when the confidence intervals did not include zero (Hayes, 2018).

Results

Direct Effects

Figure 2 displays the unstandardized path coefficients for the findings with regard to the relationships among social media use (T1), social support (T2), social capital (T2), and life satisfaction (T2). Social media use at T1 was directly associated with social support at T2 (B = 0.03, SE = 0.01, p < .01). However, social media use at T1 did not demonstrate a statistically significant direct relationship with social capital at T2 or life satisfaction at T2. The results also indicated that social support at T2 was positively associated with social capital at T2 (B = 0.60, SE = 0.03, p < .001) and life satisfaction at T2 (B = 0.32, SE = 0.07, p < .001). Finally, social capital at T2 was positively correlated with life satisfaction at T2 (B = 0.36, SE = 0.06, p < .001).

Figure 2.

Mediation model and path coefficients.

Indirect Effects

This study hypothesized the mediating mechanisms by which social media use at T1 is associated with life satisfaction at T2 through social support at T2 and/or social capital at T2. Table 1 shows the findings regarding the indirect effects of social media use at T1 on life satisfaction at T2 through the two mediating variables at T2. The findings indicated that the indirect effect of social media use at T1 on life satisfaction at T2 via social support at T2 was positive and statistically significant (B = 0.011, SE = 0.006, 95% CI [0.007, 0.034]). However, there was no significant indirect effect of social capital at T2 on the relationship between social media use at T1 and life satisfaction at T2. Lastly, this study found that the indirect path through social support and social capital at T2 in the relationship between social media use at T1 and life satisfaction at T2 was positively and statistically significant (B = 0.007, SE = 0.002, 95% CI [0.002, 0.013]) (Table 4).

Table 4.

Indirect Effects of Social Media Use on Life Satisfaction Through Social Support and Social Capital.

Indirect path	Path coefficient (SE)	CI
Social media use → social support → life satisfaction	.011 (0.006)*	[0.007, 0.034]
Social media use → social capital → life satisfaction	.001 (0.003)	[−0.005, 0.008]
Social media use → social support → social capital → life satisfaction	.007 (0.002)*	[0.002, 0.013]

Note. Unstandardized regression coefficients and corresponding standard errors are reported. CIs are bias-corrected 95% confidence intervals for the indirect effects (Bootstrap N = 5,000); T1: social media use, T2: social support, social capital, and life satisfaction; Gender and school class are included as control variables in the analysis.

Indicates significant effects.

Discussion

This study analyzed panel survey data on South Korean adolescents from two time periods to examine the relationship between social media use and life satisfaction, as well as the indirect effects of social support and social capital on the association between social media use and life satisfaction. Consequently, this study produced interesting results regarding the mediating mechanisms by which social media use is associated with life satisfaction through social support and social capital. Social media use among adolescents had a significant indirect effect on life satisfaction through social support and social capital. Social support played a significant mediating role in the association between social media use and life satisfaction. The findings of this study improve our understanding of the effects of social media use on adolescents’ life satisfaction and provide important implications for the promotion of life satisfaction in such individuals through social media.

Specifically, consistent with previous studies that found positive associations between social media use, social support, and life satisfaction (e.g., Oh et al., 2014; Oshio et al., 2020), this study demonstrated that social support plays a key role in mediating relationship between social media use and life satisfaction. This suggests that adolescents who use social media more frequently are likely to have greater social support, which is positively related to higher life satisfaction. Social media can help adolescents manage their relationships with friends and provide opportunities to receive social support from or exchange such support with online networked contacts (Mackson et al., 2019). Social media allow users to easily provide and receive social support in their social networks, such as through the exchange of personalized messages, comments on users’ posts, and the pushing of “like” buttons (Choi & Noh, 2020a), which contributes to decreasing social isolation through the fulfillment of an individual’s social need for interpersonal interaction, which, in turn, increases life satisfaction. Moreover, social support derived from social interactions among social media users can elevate self-esteem (Choi & Noh, 2020b), which in turn might be positively associated with life satisfaction (Danielsen et al., 2009). Because adolescents tend to spend significant amounts of time with friends, they consider their friends and peers to represent favorable social support groups (Colarossi, 2001). Social support through peers can positively influence adolescents’ life satisfaction, which constitutes a beneficial mental health outcome (Levin et al., 2012). Thus, this study demonstrated the benefits of social media use with regard to greater social support, which can contribute to higher life satisfaction.

Furthermore, this study demonstrated the mediating mechanism by which social media use is related to life satisfaction through social support and social capital. It also indicated that social capital is not only directly associated with life satisfaction but also partially mediates the association between social support and life satisfaction. These results indicate that the more adolescents use social media, the more likely they are to have a higher level of social support, which is related to greater social capital and, consequently, the likelihood of elevated life satisfaction. This finding suggests that social support and social capital are the driving factors mediating the relationship between social media use and life satisfaction. As social media allow adolescents to maintain contact with their friends (Bruggeman et al., 2019), social media use has a positive relationship with social support by enabling a greater exchange of emotional or informational resources through convenient methods, such as “liking,”“following,” or being “friended” (Cole et al., 2017; B. Kim & Kim, 2017). A higher level of social support is associated with greater social capital, which helps adolescents to accumulate trust and benefit from the support they receive through online social networks (Barman-Adhikari et al., 2016). As social capital fosters interpersonal relationships and prevents social exclusion and loneliness, it is positively correlated with adolescents’ life satisfaction (Arampatzi et al., 2018; S. Lee et al., 2018). This demonstrates that social capital is an important predictor of mental health factors such as life satisfaction and social media use can have an indirect positive relationship with life satisfaction by providing more opportunities for social support (e.g., Oh et al., 2014; Shensa et al., 2020), building social relationships, and offering greater access to resources such as social trust and reciprocity in online social networks (e.g., Huang et al., 2022; H. Kim & Ahn, 2023). These results offer empirical evidence of the indirect relationship between social media use and life satisfaction via social support and social capital.

Considering the findings from the above mentioned analysis, this study suggests that despite the lack of a direct association between adolescent social media use and life satisfaction, there is an indirect link between the two variables through social support and social capital. Social support plays a particularly significant role in mediating the association between social media use and life satisfaction.

The study has practical and theoretical implications. In terms of the practical implications, this study offers valuable insights for parents and educators as it can help them understand the impact of social media use. The findings of this study suggest that social media can facilitate social interactions and interpersonal trust among adolescents through networked online connections. Social media may be a useful channel for the maintenance of social relationships and the continuation of communication among adolescents when people tend to avoid offline face-to-face interactions. Thus, teachers and parents should encourage adolescents to interact with their friends and exchange social support through social media to promote their life satisfaction and psychological health.

In terms of the theoretical implications, this study emphasizes the mediating role of social support and social capital in the relationship between social media use and life satisfaction. This study highlights the benefits of social media through higher levels of social support and social capital, which can, in turn, be positively related to greater life satisfaction. This contrasts with previous studies’ negative view that social media have a detrimental impact on adolescents’ life satisfaction (e.g., de Lenne et al., 2020; Twenge, 2019). Although this study did not find any direct association between social media use and life satisfaction, it demonstrated that social support and social capital play important mediating roles between social media use and life satisfaction among adolescents. The findings of this study can improve our understanding of the mediating mechanism connecting adolescents’ social media use to life satisfaction, which represents a psychological health outcome through social support and social capital.

Limitations and Suggestions for Future Research

This study has certain limitations. First, this study used only 1 item to measure the social media use variable. This is not ideal. To reduce measurement errors and reliability problems and obtain robust results, future research should include more items regarding social media use variable.

Second, this study did not consider specific types of social media use or content when examining the impact of social media use on life satisfaction. For example, as people use social media for various reasons such as communication, news, entertainment, and commerce, different kinds of social media use may produce differing results regarding the relationship between social media use and life satisfaction. Thus, future research should consider diversity in social media use, which would enable the exploration of further dynamic mechanisms behind the impact of social media on adolescent life satisfaction.

Third, the association between social media use, social support, social capital, and life satisfaction did not establish causality. However, there is a possibility of inverse relationships among the variables, and it is possible that life satisfaction predicts social media use. Moreover, this study could not rule out the possibility that social capital affects social support. It is likely that individuals with a higher level of social capital have the resources to engage in meaningful relationships and thus obtain social support from these relationships. Nevertheless, the proposed relationship among the variables is grounded in previous findings (e.g., Lin, 2011; Zhou, 2016).

Fourth, since this study’s data were collected through face-to-face interviews, there may be social desirability bias, which is the tendency of respondents to provide socially desirable responses to make them look better to others instead of responding with their true thoughts (Dillman et al., 2009).

Fifth, it is also acknowledged that the indirect path coefficients of the mediating analysis were not large, although they were statistically significant. Perhaps, this may be because the direct path coefficients between the two variables were strong; therefore, the indirect path coefficients had a relatively smaller effect on the overall associations. Thus, despite the statistically significant relationships, the results should be interpreted with caution. Nevertheless, it is more important to have a theoretically robust model that accurately depicts the associations between the variables by contributing to the total effect of the mediating and independent variables on life satisfaction (i.e., the dependent variable), even if the indirect path coefficients are somewhat weak.

Finally, although the data analyzed in the current study were collected in 2018, the findings are significant in the post-COVID-19 era. The use of social media for connection and interaction increased during the COVID-19 outbreak when people engaged in physical distancing and had fewer opportunities for in-person interactions (e.g., Pew Research Center, 2021; Statista, 2022). The findings of the current study suggest that social media use should continue to support adolescent social interactions and communications in the post- COVID-19 era, and increase their life satisfaction through social support and social capital.

Footnotes

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This material is based on work supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2018S1A3A2074932).

Ethical Statement

This study used secondary data. Data were de-identified before release to the researcher.

ORCID iD

Doo-Hun Choi

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available in the Korean Game Panel Study repository,

References

Abbas

Mesch

(2018). Do rich teens get richer? Facebook use and the link between offline and online social capital among Palestinian youth in Israel. Information, Communication & Society, 21(1), 63–79. https://doi.org/10.1080/1369118X.2016.1261168

Ahn

(2012). Teenagers’ experiences with social network sites: Relationships to bridging and bonding social capital. The Information Society, 28(2), 99–109. https://doi.org/10.1080/01972243.2011.649394

Allan

Catts

(2014). Schools, social capital and space. Cambridge Journal of Education, 44(2), 217–228. https://doi.org/10.1080/0305764X.2013.863829

Antaramian

S. P.

Huebner

E. S.

Valois

R. F.

(2008). Adolescent life satisfaction. Applied Psychology, 57, 112–126. https://doi.org/10.1111/j.1464-0597.2008.00357.x

Antheunis

M. L.

Schouten

A. P.

Krahmer

(2016). The role of social networking sites in early adolescents’ social lives. The Journal of Early Adolescence, 36(3), 348–371. https://doi.org/10.1177/0272431614564060

Arampatzi

Burger

M. J.

Novik

(2018). Social network sites, individual social capital and happiness. Journal of Happiness Studies, 19(1), 99–122. https://doi.org/10.1007/s10902-016-9808-z

Barman-Adhikari

Bowen

Bender

Brown

Rice

(2016). A social capital approach to identifying correlates of perceived social support among homeless youth. Child Youth Care Forum, 45, 691–708. https://doi.org/10.1007/s10566-016-9352-3

Başol

(2008). Validity and reliability of the multidimensional scale of perceived social support-revised, with a Turkish sample. Social Behavior and Personality, 36(10), 1303–1313.

Best

Manktelow

Taylor

(2014). Online communication, social media and adolescent wellbeing: A systematic narrative review. Children and Youth Services Review, 41, 27–36.

10.

Bruggeman

Van Hiel

Van Hal

Van Dongen

(2019). Does the use of digital media affect psychological well-being? An empirical test among children aged 9 to 12. Computers in Human Behavior, 101, 104–113. https://doi.org/10.1016/j.chb.2019.07.015

11.

Chai

H. Y.

Niu

G. F.

Lian

S. L.

Chu

X. W.

Liu

Sun

X. J.

(2019). Why social network site use fails to promote well-being? The roles of social overload and fear of missing out. Computers in Human Behavior, 100, 85–92. https://doi.org/10.1016/j.chb.2019.05.005

12.

Chen

H. T.

(2017). The contribution of mobile social media to social capital and psychological well-being: Examining the role of communicative use, friending and self-disclosure. Computers in Human Behavior, 75, 958–965. https://doi.org/10.1016/j.chb.2017.06.011

13.

Chen

Zhang

Pan

Liu

Luo

(2017). Perceived social support and self-esteem as mediators of the relationship between parental attachment and life satisfaction among Chinese adolescents. Personality and Individual Differences, 108, 98–102. https://doi.org/10.1016/j.paid.2016.12.009

14.

Cheng

(1998). Getting the right kind of support: Functional differences in the types of social support on depression for Chinese adolescents. Journal of Clinical Pssychology, 54(6), 845–849.

15.

Cheng

Wang

H. Y.

Sigerson

Chau

C. L.

(2019). Do the socially rich get richer? A nuanced perspective on social network site use and online social capital accrual. Psychological Bulletin, 145(7), 734–764.

16.

Choi

D. H.

Noh

G. Y.

(2020a). The influence of social media use on attitude toward suicide through psychological well-being, social isolation, and social support. Information, Communication & Society, 23(10), 1427–1443. https://doi.org/10.1080/1369118X.2019.1574860

17.

Choi

D. H.

Noh

G. Y.

(2020b). Associations between social media use and suicidal ideation in South Korea: Mediating roles of social capital and self-esteem. Health Communication, 35(14), 1754–1761. https://doi.org/10.1080/10410236.2019.1663466

18.

Choi

D. H.

Shin

D. H.

(2017). A dialectic perspective on the interactive relationship between social media and civic participation: The moderating role of social capital. Information, Communication & Society, 20, 151–166. https://doi.org/10.1080/1369118X.2016.1154586

19.

Colarossi

L. G.

(2001). Adolescent gender differences in social support: Structure, function, and provider type. Social Work Research, 25(4), 233–241.

20.

Cole

D. A.

Nick

E. A.

Zelkowitz

R. L.

Roeder

K. M.

Spinelli

(2017). Online social support for young people: Does it recapitulate in-person social support; can it help? Computers in Human Behavior, 68, 456–464. https://doi.org/10.1016/j.chb.2016.11.058

21.

Coleman

(1988). Social capital in the creation of human capital. The American Journal of Sociology, 94, S95–S120. https://doi.org/10.1086/228943

22.

Colvin

Cullen

F. T.

Ven

T. V.

(2002). Coercion, social support, and crime: An emerging theoretical consensus. Criminology, 40(1), 19–42. https://doi.org/10.1111/j.1745-9125.2002.tb00948.x

23.

Danielsen

A. G.

Samdal

Hetland

Wold

(2009). School-related social support and students’ perceived life satisfaction. The Journal of Educational Research, 102(4), 303–320. https://doi.org/10.3200/JOER.102.4.303-320

24.

de Lenne

Vandenbosch

Eggermont

Karsay

Trekels

(2020). Picture-perfect lives on social media: A cross-national study on the role of media ideals in adolescent well-being. Media Psychology, 23(1), 52–78. https://doi.org/10.1080/15213269.2018.1554494

25.

Dhir

Kaur

Lonka

Tsai

C. C.

(2017). Do psychosocial attributes of well-being drive intensive Facebook use? Computers in Human Behavior, 68, 520–527. https://doi.org/10.1016/j.chb.2016.11.023

26.

Diener

E. D.

Emmons

R. A.

Larsen

R. J.

Griffin

(1985). The satisfaction with life scale. Journal of Personality Assessment, 49(1), 71–75.

27.

Diener

E. D.

Lucas

R. E.

Oishi

(2002). Subjective well-being: The science of happiness and life satisfaction. In Snyder

C. R.

Lopez

S. J.

(Eds.), The handbook of positive psychology (pp. 63–73). Oxford University Press.

28.

Dienlin

Masur

P. K.

Trepte

(2017). Reinforcement or displacement? The reciprocity of FtF, IM, and SNS communication and their effects on loneliness and life satisfaction. Journal of Computer-Mediated Communication, 22(2), 71–87. https://doi.org/10.1111/jcc4.12183

29.

Dillman

D. A.

Smyth

J. D.

Christian

L. M.

(2009). Internet, mail, and mixed-mode surveys: The tailored design method (3rd ed.). John Wiley & Sons Inc.

30.

Drouin

Reining

Flanagan

Carpenter

Toscos

(2018). College students in distress: Can social media be a source of social support? College Student Journal, 52(4), 494–504.

31.

Ellison

N. B.

Steinfield

Lampe

(2011). Connection strategies: Social capital implications of Facebook-enabled communication practices. New Media & Society, 13(6), 873–892. https://doi.org/10.1177/1461444810385389

32.

Fornell

Larcker

D. F.

(1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312

33.

Frison

Eggermont

(2016). “Harder, better, faster, stronger”: Negative comparison on Facebook and Adolescents’ life satisfaction are reciprocally related. Cyberpsychology, Behavior, and Social Networking, 19(3), 158–164. https://doi.org/10.1089/cyber.2015.0296

34.

Geraee

Eslami

A. A.

Soltani

(2019). The relationship between family social capital, social media use and life satisfaction in adolescents. Health Promotion Perspectives, 9(4), 307. https://doi.org/10.15171/hpp.2019.42

35.

Gibson

Trnka

(2020). Young people’s priorities for support on social media: “It takes trust to talk about these issues”. Computers in Human Behavior, 102, 238–247. https://doi.org/10.1016/j.chb.2019.08.030

36.

Hair

J. F.

Black

W. C.

Babin

B. J.

Anderson

R. E.

(2010). Multivariate data analysis. Pearson Education.

37.

Hall

J. A.

Kearney

M. W.

Xing

(2019). Two tests of social displacement through social media use. Information, Communication & Society, 22(10), 1396–1413. https://doi.org/10.1080/1369118X.2018.1430162

38.

Hatchel

Subrahmanyam

Negriff

(2019). Adolescent peer victimization and internalizing symptoms during emerging adulthood: The role of online and offline social support. Journal of Child and Family Studies, 28(9), 2456–2466. https://doi.org/10.1007/s10826-018-1286-y

39.

Hayes

A. F.

(2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed). Guilford Publications.

40.

Huang

Zheng

Fan

(2022). Do social networking sites promote life satisfaction? The explanation from an online and offline social capital transformation. Information Technology & People, 35(2), 703–722. https://doi.org/10.1108/ITP-03-2020-0143

41.

Kahneman

Krueger

A. B.

(2006). Developments in the measurement of subjective well-being. Journal of Economic Perspectives, 20(1), 3–24. https://doi.org/10.1257/089533006776526030

42.

Kapikiran

(2013). Loneliness and life satisfaction in Turkish early adolescents: The mediating role of self esteem and social support. Social Indicators Research, 111(2), 617–632. https://doi.org/10.1007/sl1205-012-0024-x

43.

Keresteš

Štulhofer

(2020). Adolescents’ online social network use and life satisfaction: A latent growth curve modeling approach. Computers in Human Behavior, 104, 106187. https://doi.org/10.1016/j.chb.2019.106187

44.

Kim

(2017). College students’ social media use and communication network heterogeneity: Implications for social capital and subjective well-being. Computers in Human Behavior, 73, 620–628. https://doi.org/10.1016/j.chb.2017.03.033

45.

Kim

B. J.

Linton

K. F.

Lum

(2015). Social capital and life satisfaction among Chinese and Korean elderly immigrants. Journal of Social Work, 15(1), 87–100. https://doi.org/10.1177/1468017313504699

46.

Kim

Ahn

(2023). The effect of social media on social capital and life-satisfaction in the case of college sports. Atlantic Journal of Communication, 33, 227–242. https://doi.org/10.1080/15456870.2022.2061712

47.

Kong

Zhao

You

(2012). Emotional intelligence and life satisfaction in Chinese university students: The mediating role of self-esteem and social support. Personality and Individual Differences, 53(8), 1039–1043. https://doi.org/10.1016/j.paid.2012.07.032

48.

Korea Press Foundation. (2019). Teens’ media use in Korea 2019. https://www.kpf.or.kr/front/research/consumerDetail.do

49.

Lee

J. L.

(1994). The analysis of the causal model of children’s self-perceived competence and related variables. Journal of the Korean Home Economics Association, 32(4), 193–208.

50.

Lee

J. Y.

Park

E. Y.

Kim

E. M.

(2016). A comparative study on the relationship between social networking site use and social capital among Australian and Korean youth. Journal of Youth Studies, 19(9), 1164–1183. https://doi.org/10.1080/13676261.2016.1145637

51.

Lee

Chung

J. E.

Park

(2018). Network environments and well-being: An examination of personal network structure, social capital, and perceived social support. Health Communication, 33(1), 22–31. https://doi.org/10.1080/10410236.2016.1242032

52.

Levin

K. A.

Dallago

Currie

(2012). The association between adolescent life satisfaction, family structure, family affluence and gender differences in parent–child communication. Social Indicators Research, 106(2), 287–305. https://doi.org/10.1007/sl1205-011-9804-y

53.

Peng

(2019). Transitioning through social media: International students’ SNS use, perceived social support, and acculturative stress. Computers in Human Behavior, 98, 69–79. https://doi.org/10.1016/j.chb.2019.03.011

54.

Lin

C. P.

(2011). Assessing the mediating role of online social capital between social support and instant messaging usage. Electronic Commerce Research and Applications, 10(1), 105–114.

55.

Lönnqvist

J. E.

große Deters

(2016). Facebook friends, subjective well-being, social support, and personality. Computers in Human Behavior, 55, 113–120. https://doi.org/10.1016/j.chb.2015.09.002

56.

Hampton

K. N.

(2017). Beyond the power of networks: Differentiating network structure from social media affordances for perceived social support. New Media & Society, 19(6), 861–879.

57.

Mackson

S. B.

Brochu

P. M.

Schneider

B. A.

(2019). Instagram: Friend or foe? The application’s association with psychological well-being. New Media & Society, 21(10), 2160–2182.

58.

Manago

A. M.

Melton

C. J.

(2020). Emerging adults’ Views on masspersonal self-disclosure and their bridging social capital on Facebook. Journal of Adolescent Research, 35(1), 111–146. https://doi.org/10.1177/0743558419883789

59.

Marttila

Koivula

Räsänen

(2021). Does excessive social media use decrease subjective well-being? A longitudinal analysis of the relationship between problematic use, loneliness and life satisfaction. Telematics and Informatics, 59, 101556. https://doi.org/10.1016/j.tele.2020.101556

60.

Noh

G.-Y.

Lee

S. Y.

Choi

(2016). Exploring factors influencing smokers’ information seeking for smoking cessation. Journal of Health Communication, 21(8), 845–854. https://doi.org/10.1080/10810730.2016.1177140

61.

H. J.

Ozkaya

LaRose

(2014). How does online social networking enhance life satisfaction? The relationships among online supportive interaction, affect, perceived social support, sense of community, and life satisfaction. Computers in Human Behavior, 30, 69–78. https://doi.org/10.1016/j.chb.2013.07.053

62.

Oshio

Kimura

Nishizaki

Omori

(2020). Association between the use of social networking sites, perceived social support, and life satisfaction: Evidence from a population-based survey in Japan. PLOS ONE, 15(12), e0244199. https://doi.org/10.1371/journal.pone.0244199

63.

Park

Roh

Yeo

(2012). Religiosity, social support, and life satisfaction among elderly Korean immigrants. The Gerontologist, 52(5), 641–649.

64.

Pang

(2018). Understanding the effects of WeChat on perceived social capital and psychological well-being among Chinese international college students in Germany. Aslib Journal of Information Management, 70(3), 288–304. https://doi.org/10.1108/AJIM-01-2018-0003

65.

Pew Research Center. (2018). Teens, social media & technology 2018. https://www.pewresearch.org/internet/2018/05/31/teens-social-media-technology-2018/

66.

Pew Research Center. (2021). Social media use in 2021. https://www.pewresearch.org/internet/2021/04/07/social-media-use-in-2021/

67.

Phua

Jin

S. V.

Kim

J. J.

(2017). Uses and gratifications of social networking sites for bridging and bonding social capital: A comparison of Facebook, Twitter, Instagram, and Snapchat. Computers in Human Behavior, 72, 115–122. https://doi.org/10.1016/j.chb.2017.02.041

68.

Primack

B. A.

Colditz

J. B.

Cohen

Switzer

G. E.

Robinson

G. F.

Seltzer

D. L.

Rubio

D. M.

Kapoor

W. N.

(2014). Measurement of social capital among clinical research trainees. Clinical and Translational Science, 7(1), 33–37.

69.

Putnam

R. D.

(2000). Bowing alone: The collapse and revival of American community. Simon & Schuster.

70.

Quan-Haase

G. Y.

Wellman

(2017). Connected seniors: How older adults in East York exchange social support online and offline. Information, Communication & Society, 20(7), 967–983.

71.

Schemer

Masur

P. K.

Geiß

Müller

Schäfer

(2021). The impact of internet and social media use on well-being: A longitudinal analysis of adolescents across nine years. Journal of Computer-Mediated Communication, 26(1), 1–21. https://doi.org/10.1093/jcmc/zmaa014

72.

Shensa

Sidani

J. E.

Escobar-Viera

C. G.

Switzer

G. E.

Primack

B. A.

Choukas-Bradley

(2020). Emotional support from social media and face-to-face relationships: Associations with depression risk among young adults. Journal of Affective Disorders, 260, 38–44. https://doi.org/10.1016/j.jad.2019.08.092

73.

C. C.

Chan

N. K.

(2017). Predicting social capital on Facebook: The implications of use intensity, perceived content desirability, and Facebook-enabled communication practices. Computers in Human Behavior, 72, 259–268. https://doi.org/10.1016/j.chb.2017.02.058

74.

Shen

Yeatts

D. E.

(2013). Social support and life satisfaction among older adults in China: Family-based support versus community-based support. The International Journal of Aging and Human Development, 77(3), 189–209. http://dx.doi.org/10.2190/AG.77.3.b

75.

Spreng

R. A.

MacKenzie

S. B.

Olshavsky

R. W.

(1996). A reexamination of the determinants of consumer satisfaction. Journal of Marketing, 60(3), 15–32. https://doi.org/10.2307/1251839

76.

Statista. (2022). Social media use during COVID-19 worldwide: Statistics & facts. https://www.statista.com/topics/7863/social-media-use-during-coronavirus-covid-19-worldwide/#topicOverview

77.

Twenge

J. M.

(2019). More time on technology, less happiness? Associations between digital-media use and psychological well-being. Current Directions in Psychological Science, 28(4), 372–379. https://doi.org/10.1177/0963721419838244

78.

Twenge

J. M.

Campbell

W. K.

(2018). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive Medicine Reports, 12, 271–283. https://doi.org/10.1016/j.pmedr.2018.10.003

79.

Urberg

Goldstein

M. S.

Toro

P. A.

(2005). Supportive relationships as a moderator of the effects of parent and peer drinking on adolescent drinking. Journal of Research on Adolescence, 15(1), 1–19.

80.

Valkenburg

P. M.

Peter

(2007). Online communication and adolescent well-being: Testing the stimulation versus the displacement hypothesis. Journal of Computer-Mediated Communication, 12(4), 1169–1182. https://doi.org/10.1111/j.1083-6101.2007.00368.x

81.

Valenzuela

Park

Kee

K. F.

(2009). Is there social capital in a social network site? Facebook use and college students’ life satisfaction, trust, and participation. Journal of Computer-Mediated Communication, 14, 875–901. https://doi.org/10.1111/j.10836101.2009.01474.x

82.

Weinstein

(2018). The social media see-saw: Positive and negative influences on adolescents’ affective well-being. New Media & Society, 20(10), 3597–3623. https://doi.org/10.1177/1461444818755634

83.

Williams

(2006). On and off the Net: Scales for social capital in an online era. Journal of Computer-Mediated Communication, 11(2), 593–628.

84.

Williams

J. R.

(2019). The use of online social networking sites to nurture and cultivate bonding social capital: A systematic review of the literature from 1997 to 2018. New Media & Society, 21(11–12), 2710–2729. https://doi.org/10.1177/1461444819858749

85.

Wohn

D. Y.

Carr

C. T.

Hayes

R. A.

(2016). How affective is a “Like”?: The effect of paralinguistic digital affordances on perceived social support. Cyberpsychology, Behavior, and Social Networking, 19(9), 562–566.

86.

Yen

Y. S.

(2016). Perceived social support moderates the relationships between variables in the social cognition model. Behaviour & Information Technology, 35(6), 479–489. https://doi.org/10.1080/0144929X.2016.1155236

87.

Yoo

(2019). How risk communication via Facebook and Twitter shapes behavioral intentions: The case of fine dust pollution in South Korea. Journal of Health Communication, 24(7–8), 663–673. https://doi.org/10.1080/10810730.2019.1655607

88.

Ziv

Kiasi

(2016). Facebook’s contribution to well-being among adolescent and young adults as a function of mental resilience. The Journal of Psychology, 150(4), 527–541. https://doi.org/10.1080/00223980.2015.1110556

89.

Zhong

Z. J.

(2014). Civic engagement among educated Chinese youth: The role of SNS (Social Networking Services), bonding and bridging social capital. Computers & Education, 75, 263–273. https://doi.org/10.1016/j.compedu.2014.03.005

90.

Zhou

(2016). Examining social capital on mobile SNS: The effect of social support. Program: Electronic Library and Information Systems, 50(4), 367–379.