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.
Revised: September 14, 2012 |
Published: May 1, 2012
Citation
Engel D.W., M.L. Gregory, E.B. Bell, and L.R. McGrath. 2012.IDENTIFYING ON-LINE GROUPS BASED ON CONTENT AND COLLECTIVE BEHAVIORAL PATTERNS. In IADIS International Conference Web Based Communities and Social Media, July 22-24, 2011, Rome, Italy. N.P.:IADIS Press.PNNL-SA-79593.