Discovering Habits of Effective Online Support Group Chatrooms

Simple item page
dc.contributor.authorMayfield, Elijah
dc.contributor.authorWen, Miaomiao
dc.contributor.authorGolant, Mitch
dc.contributor.authorPenstein Rosé, Carolyn
dc.date.accessioned2023-06-08T11:45:09Z
dc.date.available2023-06-08T11:45:09Z
dc.date.issued2012
dc.description.abstractFor 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.en
dc.identifier.doi10.1145/2389176.2389216
dc.identifier.urihttps://dl.eusset.eu/handle/20.500.12015/4946
dc.language.isoen
dc.publisherAssociation for Computing Machinery
dc.relation.ispartofProceedings of the 2012 ACM International Conference on Supporting Group Work
dc.subjectsentiment analysis
dc.subjectsocial media
dc.subjectefficacy
dc.subjectsynchronous chat
dc.subjectdiscourse analysis
dc.subjectinformation exchange
dc.subjectgroup dynamics
dc.titleDiscovering Habits of Effective Online Support Group Chatroomsen
gi.citation.publisherPlaceNew York, NY, USA
gi.citation.startPage263–272
gi.conference.locationSanibel Island, Florida, USA

Files

Collections

GROUP 2012