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The dark side of social media platforms: A situation-organism-behaviour-consequence approach

Fauzia Jabeen, Anushree Tandon, Nasreen Azad, A.K.M. Najmul Islam and Vijay Pereira

Technological Forecasting and Social Change, 2023, vol. 186, issue PA

Abstract: Research indicates that social media platform (SMP) use may adversely influence university students' academic performance (AP)—a phenomenon broadly known as the dark side of social media (DoSM). Our study applies the Situation-Organism-Behaviour-Consequence (S-O-B-C) framework to explicate pathways through which situational triggers (loneliness and self-presentation) lead to students' experience of cognitive (information and communication) overload, addiction (SMA), and consequentially, reduced academic performance (RAP). Methodologically, we deploy a mixed-methods approach comprising three studies—a qualitative study (Study A, n = 48) and two quantitative, cross-sectional studies in India (Study B: n = 479, Study C: n = 618)—through convenience sampling to develop and test a conceptual model through PLS-SEM. Our results provide evidence that loneliness and students' self-presentation significantly influence overload and SMA, which strongly influence RAP. Additionally, a partial moderating effect of demotivation due to social comparison was found in Study C, lending nuanced insight into the effects of personal tendencies on students' SMP use. Our study is limited to an emerging country context, but the results raise practical implications for students across the globe. In addition, our study suggests that future scholars should further investigate the personal and situational factors that can affect students' DoSM experiences like cognitive overload.

Keywords: Loneliness; Self-presentation; Social media overload; Academic performance; Social media addiction (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:186:y:2023:i:pa:s0040162522006254

DOI: 10.1016/j.techfore.2022.122104

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