Understanding moderation in online mental health communities

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Abstract

Online Mental Health Communities (OMHCs) enable individuals to seek and provide support, and serve as a safe haven to disclose and share stigmatizing and sensitive experiences. Like other online communities, OMHCs are not immune to bad behavior and antisocial activities such as trolling, spamming, and harassment. Therefore, these communities are oftentimes guided by strict norms against such behavior, and moderated to ensure the quality and credibility of the content being shared. However, moderation within these communities is not only limited to ensuring content quality. It is far more complex—providing supportive spaces for disclosure, ensuring individuals’ privacy, etc.—because of the sensitive population that they cater to. By interviewing 19 moderators across 12 such OMHCs on Reddit, this paper studies the practices and structure of moderation in these communities to better understand their functioning and effectiveness. Our research questions primarily revolve around three major themes—moderation, support, and self-disclosure. We find practices of moderation hierarchy, and several distinctions in motivations and responsibilities of the moderators individually and as a group. We also notice that these communities predominantly encourage emotional support, and provide supportive spaces that encourage self-disclosure on stigmatized concerns. Our findings highlight the necessity of awareness corresponding to (currently lacking) privacy concerns, and raises the importance of the presence of mental health experts (counselors and psychiatrists) in these communities. On the basis of the insights drawn from this work, we discuss the implications and considerations for designing OMHCs.

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APA

Saha, K., Ernala, S. K., Dutta, S., Sharma, E., & De Choudhury, M. (2020). Understanding moderation in online mental health communities. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12195 LNCS, pp. 87–107). Springer. https://doi.org/10.1007/978-3-030-49576-3_7

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