Abstract

Community discovery in social networks has received a significant amount of attention in the social media research community. The techniques developed by the community have become quite adept at identifying the large communities in a network, but often neglect smaller communities. Evaluation techniques also show this bias, as the resolution limit problem in modularity indicates. Small communities, however, account for a higher proportion of a social network's community membership and reveal important information about the members of these communities. In this work, we introduce a re-weighting method to improve both the overall performance of community detection algorithms and performance on small community detection.

Original languageEnglish (US)
Title of host publicationProceedings of the 10th International Conference on Web and Social Media, ICWSM 2016
PublisherAAAI Press
Pages603-606
Number of pages4
ISBN (Electronic)9781577357582
StatePublished - 2016
Event10th International Conference on Web and Social Media, ICWSM 2016 - Cologne, Germany
Duration: May 17 2016May 20 2016

Other

Other10th International Conference on Web and Social Media, ICWSM 2016
CountryGermany
CityCologne
Period5/17/165/20/16

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Jones, I., Wang, R., Han, J., & Liu, H. (2016). Community cores: Removing size bias from community detection. In Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016 (pp. 603-606). AAAI Press.