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Hyper-community detection in the blogosphere

Nguyen, Thin, Phung, Dinh, Adams, Brett, Tran, Truyen and Venkatesh, Svetha 2010, Hyper-community detection in the blogosphere, in WSM 2010 : Proceedings of the 2nd ACM SIGMM Workshop on Social Media, ACM, New York, N. Y., pp. 21-26.

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Title Hyper-community detection in the blogosphere
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
Tran, TruyenORCID iD for Tran, Truyen orcid.org/0000-0001-6531-8907
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Conference name ACM SIGMM Workshop on Social Media (2nd : 2010 : Firenze, Italy)
Conference location Firenze, Italy
Conference dates 25 Oct. 2010
Title of proceedings WSM 2010 : Proceedings of the 2nd ACM SIGMM Workshop on Social Media
Editor(s) [Unknown]
Publication date 2010
Conference series ACM SIGMM Workshop on Social Media
Start page 21
End page 26
Total pages 6
Publisher ACM
Place of publication New York, N. Y.
Keyword(s) content-based
hyper-community
sentiment-based
social media
Summary Most existing work on learning community structure in social network is graph-based whose links among the members are often represented as an adjacency matrix, encoding direct pairwise associations between members. In this paper, we propose a method to group online communities in blogosphere based on the topics learnt from the content blogged. We then consider a different type of online community formulation - the sentiment-based grouping of online communities. The problem of sentiment-based clustering for community structure discovery is rich with many interesting open aspects to be explored. We propose a novel approach for addressing hyper-community detection based on users' sentiment. We employ a nonparametric clustering to automatically discover hidden hyper-communities and present the results obtained from a large dataset.
ISBN 9781450301732
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2010, ACM
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044549

Document type: Conference Paper
Collection: School of Information Technology
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