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Addiction to social networking sites: Motivations, flow, and sense of belonging at the root of addiction

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  • Miranda, Sandra
  • Trigo, Inês
  • Rodrigues, Ricardo
  • Duarte, Margarida

Abstract

The adverse effects of excessive and problematic social networking sites (SNSs) use are well described in academic and practitioner literature. However, it remains unclear how these problematic uses arise. By exploring the phenomenon of SNS addiction, this paper identifies how the problematic use of an SNS emerges and develops. We hypothesize that the flow state induced by using SNSs and the sense of belonging are two mediators of the influence of the user's motivations on the development of an SNS addiction. We used variance-based structural equation modeling (PLS-SEM) to analyze data collected from a sample of TikTok SNS users and test the research hypotheses. The results suggest that different addiction mechanisms are associated with different motivations to continue using the social network. This research brings new insights to the social media addiction literature by identifying one new alternative addiction mechanism – via the sense of belonging – by which addiction to social networks can develop. Such knowledge may help inform social networking providers and organizations of social media users' engagement triggers. It also helps inform public health officials on how to help users overcome addictive behaviors on social media.

Suggested Citation

  • Miranda, Sandra & Trigo, Inês & Rodrigues, Ricardo & Duarte, Margarida, 2023. "Addiction to social networking sites: Motivations, flow, and sense of belonging at the root of addiction," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    • Handle: RePEc:eee:tefoso:v:188:y:2023:i:c:s0040162522008010
    DOI: 10.1016/j.techfore.2022.122280
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    1. Pang, Hua & Ruan, Yang & Zhang, Kaige, 2024. "Deciphering technological contributions of visibility and interactivity to website atmospheric and customer stickiness in AI-driven websites: The pivotal function of online flow state," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    2. Pang, Hua & Qiao, Yuxin & Zhang, Kaige, 2024. "Modeling pathway linking mobile social media intensity to attitude towards electronic word-of-mouth and engagement: The significant role of social trust and perceived homophily," Technological Forecasting and Social Change, Elsevier, vol. 198(C).

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