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

Conference · Sun Jul 17 00:00:00 EDT 2011

OSTI ID:1038398

Gregory, Michelle L; Engel, David W; Bell, Eric B; Piatt, Andrew W; Dowson, Scott T; Cowell, Andrew J

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.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1038398
• Report Number(s): PNNL-SA-78096; TRN: US201208%%488
• Resource Relation: Conference: Proceedings of the Fifth International Conference on Weblogs and Social Media, July 17-21, 2011, Barcelona, Spain, 498-501
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
COMMUNITIES
EIGENVALUES
INTERNET