Together Apart: Decoding Support Dynamics in Online COVID-19 Communities
Authors: 
Hitkul Jangid, Tanisha Pandey, Sonali Singhal, Pranjal Kandhari, Aryamann Tomar, Ponnurangam KumaraguruAuthors Info & Claims
Hitkul Jangid, Tanisha Pandey, Sonali Singhal, Pranjal Kandhari, Aryamann Tomar, Ponnurangam KumaraguruAuthors Info & ClaimsPages 263 - 270
Abstract
The COVID-19 pandemic that broke out globally in December 2019 put us all in an unprecedented situation. Social media became a vital source of support and information during the pandemic, as physical interactions were limited by people staying at home. This paper investigates support dynamics and user commitment in an online COVID-19 community of Reddit. We define various support classes and observe them along with user behavior and temporal phases for a coherent in the community. We perform survival analysis using Cox Regression to identify factors influencing a user's commitment to the community. People seeking more emotional and informational support while they are COVID-positive stay longer in the community. Surprisingly, people who give more support in their early phases are less likely to stay. Additionally, contrary to common belief, our findings show that receiving emotional and informational support has little effect on users' longevity in the community. Our results lead to a better understanding of user dynamics related to community support and can directly impact moderators and platform owners in designing community guidelines and incentive structures.
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- Together Apart: Decoding Support Dynamics in Online COVID-19 Communities
Index terms have been assigned to the content through auto-classification.
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Published: 15 March 2024
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