A sentiment-aware approach to community formation in social media

Nguyen, Thin, Phung, Dinh, Adams, Brett and Venkatesh, Svetha 2012, A sentiment-aware approach to community formation in social media, in ICWSM 2012 : Proceedings of the Sixth International Conference on Weblogs and Social Media, Association for the Advancement of Artificial Intelligence (AAAI), [Dublin, Ireland], pp. 527-530.

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Title A sentiment-aware approach to community formation in social media
Author(s) Nguyen, ThinORCID iD for Nguyen, Thin orcid.org/0000-0003-3467-8963
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Adams, Brett
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Conference name Weblogs and Social Media. International Conference ( 6th : 2012 : Dublin, Ireland)
Conference location Dublin, Ireland
Conference dates 4-7 Jun. 2012
Title of proceedings ICWSM 2012 : Proceedings of the Sixth International Conference on Weblogs and Social Media
Editor(s) [Unknown]
Publication date 2012
Conference series International Conference on Weblogs and Social Media
Start page 527
End page 530
Total pages 4
Publisher Association for the Advancement of Artificial Intelligence (AAAI)
Place of publication [Dublin, Ireland]
Summary 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 metacommunities, 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.
Language eng
Field of Research 080305 Multimedia Programming
Socio Economic Objective 899999 Information and Communication Services not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30052647

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