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Critical Behavioral Traits Foster Peer Engagement in Online Mental Health Communities

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arxiv 2309.01618 v1 pith:4XWYCFXN submitted 2023-09-04 cs.CL

classification cs.CL
keywords mentalhealthengagementpeerplatformsassistancebehaviorcommunities
verification ladder T0 review T1 audit T2 compute T3 formal
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Online Mental Health Communities (OMHCs), such as Reddit, have witnessed a surge in popularity as go-to platforms for seeking information and support in managing mental health needs. Platforms like Reddit offer immediate interactions with peers, granting users a vital space for seeking mental health assistance. However, the largely unregulated nature of these platforms introduces intricate challenges for both users and society at large. This study explores the factors that drive peer engagement within counseling threads, aiming to enhance our understanding of this critical phenomenon. We introduce BeCOPE, a novel behavior encoded Peer counseling dataset comprising over 10,118 posts and 58,279 comments sourced from 21 mental health-specific subreddits. The dataset is annotated using three major fine-grained behavior labels: (a) intent, (b) criticism, and (c) readability, along with the emotion labels. Our analysis indicates the prominence of ``self-criticism'' as the most prevalent form of criticism expressed by help-seekers, accounting for a significant 43% of interactions. Intriguingly, we observe that individuals who explicitly express their need for help are 18.01% more likely to receive assistance compared to those who present ``surveys'' or engage in ``rants.'' Furthermore, we highlight the pivotal role of well-articulated problem descriptions, showing that superior readability effectively doubles the likelihood of receiving the sought-after support. Our study emphasizes the essential role of OMHCs in offering personalized guidance and unveils behavior-driven engagement patterns.

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Cited by 1 Pith paper

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  1. Trust Modeling in Counseling Conversations: A Benchmark Study

    cs.CL 2025-01 conditional novelty 6.0 of 10

    Introduces MENTAL-TRUST, a seven-level expert-annotated trust dataset for counseling dialogues, and benchmarks 14 models, reporting that fine-tuned smaller models outperform zero-shot LLMs.

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