@inproceedings{d71c132170d94b3181dbb8deb6cc5f9d,
title = "Community cores: Removing size bias from community detection",
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.",
author = "Isaac Jones and Ran Wang and Jiawei Han and Huan Liu",
note = "Publisher Copyright: {\textcopyright} Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 10th International Conference on Web and Social Media, ICWSM 2016 ; Conference date: 17-05-2016 Through 20-05-2016",
year = "2016",
language = "English (US)",
series = "Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016",
publisher = "American Association for Artificial Intelligence (AAAI) Press",
pages = "603--606",
booktitle = "Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016",
address = "United States",
}