Integrating sociotechnical systems theory to examine deviant behavior on social media: an empirical analysis of computer science students

Purpose This study examines how individual and sociotechnical factors, operationalized as Social Engagement (SCE), shape privacy and security risks, which subsequently influence Deviant Behavior on Social Media (DBS). Grounded in Sociotechnical Systems Theory (STS), SCE is modeled as a hybrid construct capturing social interactions and platform design features. Design/methodology/approach A quantitative survey of 305 university students (purposive sampling) was analyzed using PLS-SEM. Findings Personal Traits, Invisibility, and SCE significantly increased privacy risk, while Social Identity, Homophily, User-to-User Interaction, and SCE increased security risk. Both risks fully mediate these effects on DBS. The model explains 64.3% of the variance in DBS, underscoring the role of socio-technical engagement in shaping deviant behavior. Research limitations/implications The purposive sample of high-literacy students limits generalizability to younger adolescents. Future research should adopt longitudinal designs and test diverse populations. Practical implications Insights are provided for platform designers to mitigate deviant behaviors through enhanced privacy settings, risk alerts, and user education. Social implications The findings emphasize digital literacy and privacy awareness to foster safer online environments and responsible citizenship. Originality/value By integrating STS with a hybrid SCE construct and dual risk pathways, this study clarifies the mechanism through which socio-technical engagement translates into DBS.