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Automatically Identifying Groups Based on Content and Collective Behavioral Patterns of Group Members

Authors

Michelle Gregory,Dave Engel,Eric Bell,Andy Piatt,Scott Dowson,Andrew Cowell

Pacific Northwest National Laboratory,Pacific Northwest National Laboratory,Pacific Northwest National Laboratory,Pacific Northwest National Laboratory,Pacific Northwest National Laboratory,Pacific Northwest National Laboratory


Proceedings:

Proceedings of the International AAAI Conference on Web and Social Media, 5

Volume

Issue:

Vol. 5 No. 1 (2011): Fifth International AAAI Conference on Weblogs and Social Media

Track:

Poster Papers

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Abstract:

Online communities, or groups, have largely been defined based on links, page rank, and eigenvalues. In this paper we explore identifying abstract groups, groups where member’s interests and online footprints are similar but they are not necessarily connected to one another explicitly. We use a combination of structural information and content information from posts and their comments to build a footprint for groups. We find that these variables do a good job at identifying groups, placing members within a group, and help determine the appropriate granularity for group boundaries.

DOI:

10.1609/icwsm.v5i1.14155


ICWSM

Vol. 5 No. 1 (2011): Fifth International AAAI Conference on Weblogs and Social Media