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Discovering Habits of Effective Online Support Group Chatrooms

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Association for Computing Machinery


For users of online support groups, prior research has suggested that a positive social environment is a key enabler of coping. Typically, demonstrating such claims about social interaction would be approached through the lens of sentiment analysis. In this work, we argue instead for a multifaceted view of emotional state, which incorporates both a static view of emotion (sentiment) with a dynamic view based on the behaviors present in a text. We codify this dynamic view through data annotations marking information sharing, sentiment, and coping efficacy. Through machine learning analysis of these annotations, we demonstrate that while sentiment predicts a user's stress at the beginning of a chat, dynamic views of efficacy are stronger indicators of stress reduction.


Mayfield, Elijah; Wen, Miaomiao; Golant, Mitch; Penstein Rosé, Carolyn (2012): Discovering Habits of Effective Online Support Group Chatrooms. Proceedings of the 2012 ACM International Conference on Supporting Group Work. DOI: 10.1145/2389176.2389216. New York, NY, USA: Association for Computing Machinery. pp. 263–272. Sanibel Island, Florida, USA