This paper addresses the challenge of identifying active subgroups within online communities, a key task as these digital spaces continue to grow and evolve. Utilizing k-plex analysis and hierarchical clustering, the study explores the dynamics of the TorCamp Google group community to identify and contrast its active subgroups. The effectiveness of this methodology is validated by comparing the identified subgroups with members' self-reported sense of community and acquaintanceships. Findings reveal that these active subgroups not only engage more frequently with each other but also share a stronger sense of community. The study concludes that automated tools for analyzing online social networks can effectively detect active subgroups, offering valuable insights for understanding and enhancing online community dynamics.
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Chin, Alvin, and Mark Chignell. "Identifying active subgroups in online communities." Proceedings of the 2007 conference of the center for advanced studies on Collaborative research. 2007.
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