Mayfield, ElijahWen, MiaomiaoGolant, MitchPenstein Rosé, Carolyn2023-06-082023-06-082012https://dl.eusset.eu/handle/20.500.12015/4946For 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.ensentiment analysissocial mediaefficacysynchronous chatdiscourse analysisinformation exchangegroup dynamics10.1145/2389176.2389216