Social Media Use and Depression:The Mediating Effects of Social Comparison and Social Exclusion
Author: Wen-Tzu Chiang (Department of Social Psychology, Shih Hsin University)
Vol.&No.：Vol. 70, No. 2
Date：June 2025
Pages：273-305
DOI：https://doi.org/10.6209/JORIES.202506_70(2).0008
Abstract：
Introduction
In the digital era, interacting with others and sharing information through social media has become integral to daily life. Social media creates a sense of proximity across vast distances, enabling users to share experiences and gain social capital. However, it can also lead to social overload and social comparison, which may reduce well-being (Fox & Moreland, 2015) and even give rise to phenomena such as “social media depression” or “Facebook depression” (Blease, 2015). While social media provides positive benefits, it also has negative consequences, evoking joy and distress. The ongoing debate about whether social media use causes depression resembles a back-and-forth “ping-pong effect,” making it a topic worthy of deeper investigation.
According to existing literature, the primary mechanisms linking social media use to depression are social comparison and envy (Aubry et al., 2024; Tandoc & Goh, 2023). Social media serves as a platform for gaining social capital but also as a competitive social arena. Accumulating followers, receiving numerous likes and comments on posts, and achieving high visibility are often perceived as indicators of popularity and social status, leading individuals to compare popularity and approval (Blease, 2015; Diefenbach & Anders, 2022). Additionally, social media is a stage for self-presentation, where users share their achievements and highlight the positive aspects of their lives. This, in turn, can trigger envy among viewers. Frequent exposure to others’ success increases opportunities for social comparison, and if individuals experience feelings of failure, it may lead to depressive symptoms (Alfasi, 2019; Appel et al., 2016).
In addition to social comparison, social exclusion on social media may also contribute to depression. As a platform for social connection, social media can also be a site for rejection, neglect, and negative feedback, leading to emotional distress (Smith et al., 2017). For example, receiving no likes or comments on posts or being unfollowed can result in negative emotions (Hayes et al., 2018). Negative comments, cyberbullying, or exclusionary experiences may further amplify psychological distress and increase the risk of depression.
A comprehensive review of the literature suggests that social comparison and social exclusion play significant roles in the relationship between social media use and depression. The sources of depressive symptoms associated with social media use involve both internal (social comparison) and external (social exclusion) factors or even a combination of both. To address the limitations of prior research, which often focused on a single mediating factor, this study proposes a dual mediation model to examine the mediating effects of social comparison and social exclusion, thereby providing a more comprehensive understanding of how social media use influences mental health.
Methods
With the continuous evolution of social media platforms, research has predominantly focused on Facebook due to its long history and large user base. However, college students now primarily use Instagram to share photos, post updates, view stories, and follow friends. This study specifically examines the use of Instagram and its impact on the mental health of college students.
This study proposes a dual mediation model in which social media use influences depression through two mediating mechanisms: social comparison and social exclusion. A survey method was employed to collect data using the following research instruments: Social Media Use Scale, Social Comparison Scale, Social Exclusion Scale, and Depression Scale. The study targeted college students who use Instagram, with a final sample of 345 valid responses. Structural equation modeling (SEM) was utilized to test the mediation model.
Results
(1) Model fit evaluation: The proposed mediation model demonstrated an acceptable fit to the data. Fit indices were as follows: χ² (30, N = 345) = 86.29 (p < .01), χ²/df = 2.87( less than 3, within an acceptable range). Absolute fit indices showed GFI = .95, AGFI = .91 (both > .90), RMSEA = .07, and SRMR = .06 (both < .08). Incremental fit indices were CFI = .96, NFI = .94, RFI = .91, IFI = .96, all above .90.
(2) Social media use intensity predicts social comparison and social exclusion: Social media use intensity significantly predicted social comparison (γ = .68, p < .01). Higher social media engagement increased exposure to others’ curated lives, fostering more frequent social comparisons. Social media use intensity also significantly predicted social exclusion (γ = .46, p < .01).
(3) Social comparison and social exclusion predict depression: Social comparison significantly predicted depression (β = .36, p < .01). Users who frequently compared themselves to others and perceived others’ success as their failure exhibited more significant depressive symptoms. Social exclusion significantly predicted depression (β = .47, p < .01). Experiences of rejection, being ignored, unfollowed, or receiving negative feedback contributed to depressive symptoms.
(4) Mediating effects of social comparison and social exclusion: Without mediators, the direct effect of social media use on depression was γ = .46 (p < .01). After including social comparison and social exclusion as mediators, the direct effect decreased to γ = .03 (p > .05), indicating complete mediation. The indirect effect of social media use on depression through social comparison was β = .25 (p < .01). The indirect effect of social media use on depression through social exclusion was β = .22 (p < .01). Both mediation effects were significant, confirming the dual mediation model.
Conclusion
This study supports the proposed dual mediation model, demonstrating that social media use increases the risk of depression through heightened social comparison and social exclusion. The findings contribute to both academic research and practical implications. However, some limitations must be acknowledged. First, this study utilized structural equation modeling (SEM) with cross-sectional data, making causal inferences cautious. Future research should adopt longitudinal or experimental designs to clarify causal relationships. Second, while this study focused on Instagram, different social media platforms (e.g., Threads) may function differently, warranting further investigation. Additionally, the sample consisted of undergraduate students, which limits generalizability. Future research should explore whether similar patterns emerge in different age groups and across other social media platforms.
Keywords：
social comparison, social exclusion, social media, depression