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Title: Matching for Peer Support: Exploring Algorithmic Matching for Online Mental Health Communities
Online mental health communities (OMHCs) have emerged in recent years as an effective and accessible way to obtain peer support, filling crucial gaps of traditional mental health resources. However, the mechanisms for users to find relationships that fulfill their needs and capabilities in these communities are highly underdeveloped. Using a mixed-methods approach of user interviews and behavioral log analysis on 7Cups.com, we explore central challenges in finding adequate peer relationships in online support platforms and how algorithmic matching can alleviate many of these issues. We measure the impact of using qualities like gender and age in purposeful matching to improve member experiences, with especially salient results for users belonging to vulnerable populations. Lastly, we note key considerations for designing matching systems in the online mental health context, such as the necessity for better moderation to avoid potential harassment behaviors exacerbated by algorithmic matching. Our findings yield key insights into current user experiences in OMHCs as well as design implications for building matching systems in the future for OMHCs.  more » « less
Award ID(s):
2000782 2001851 1952085 1939606
PAR ID:
10408806
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Proceedings of the ACM on Human-Computer Interaction
Volume:
6
Issue:
CSCW2
ISSN:
2573-0142
Page Range / eLocation ID:
1 to 37
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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