Proceedings:
Proceedings of the International AAAI Conference on Web and Social Media, 6
Volume
Issue:
Vol. 6 No. 1 (2012): Sixth International AAAI Conference on Weblogs and Social Media
Track:
Poster Papers
Downloads:
Abstract:
Participating in a community exemplifies the aspect of sharing, networking and interacting in a social media system. There has been extensive work on characterising on-line communities by their contents and tags using topic modelling tools. However, the role of sentiment and mood has not been studied. Arguably, mood is an integral feature of a text, and becomes more significant in the context of social media: two communities might discuss precisely the same topics, yet within an entirely different atmosphere. Such sentiment-related distinctions are important for many kinds of analysis and applications, such as community recommendation. We present a novel approach to identification of latent hyper-groups in social communities based on users’ sentiment. The results show that a sentiment-based approach can yield useful insights into community formation and meta-communities, having potential applications in, for example, mental health—by targeting support or surveillance to communities with negative mood—or in marketing—by targeting customer communities having the same sentiment on similar topics.
DOI:
10.1609/icwsm.v6i1.14290
ICWSM
Vol. 6 No. 1 (2012): Sixth International AAAI Conference on Weblogs and Social Media