Until now, little has been known about social media’s use on subjective well-being since there are no consistent results. For example, Jung et al. (2017) reported that overusing social media has a negative impact on users’ subjective well-being, whereas Skues et al. (2012) reported that social media reduces users’ levels of loneliness and improves their levels of subjective well-being. On the positive side, Johnson, Tanner, Lalla, and Kawalski (2013) suggested that social media can be used to maintain young people’s social capital, thus improving their subjective well-being. However, a recent meta-analysis by Liu, Baumeister, Yang, and Hu (2019) pointed out that social media use could harm users’ subjective well-being. However, heavy users of Facebook, Twitter, and Instagram seem to decrease their levels of subjective well-being, specifically, by increasing negative affective states rather than by decreasing positive states or life satisfaction—a pattern evident across all these three platforms (Wirtz, Tucker, Briggs, & Schoemann, 2021). Furthermore, Ye, Ho, and Zerbe (2021) indicated that the effects of these three platforms on users’ subjective well-being might be different due to their different use patterns and the people who they followed, as the users of Twitter only seemed to have the lowest levels of subjective well-being and highest levels of loneliness, whereas users of all the three platforms had the highest levels of subjective well-being and lowest levels of loneliness.
Trust also plays a role in people’s social media use; for example, deciding to follow another user or forward a message on social media is dependent on the degree of trust between the person and the source of the message (Abdullah, Nishioka, Tanaka, & Murayama, 2015). Furthermore, social media can be a tool for emotional expressions, as can be observed in posts and messages disseminated through such social media as Facebook and Twitter. In this way, social media can play a vital role in maintaining relationships. For example, an emotional message on Twitter could influence readers to be more likely to retweet the message and retweet it more quickly (Stieglitz & Linh, 2013).