Community Detection in Social Networks through Community Formation Games
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2576-2580.
Abstract
We introduce a game-theoretic framework to address the community detection problem based on the social networks’ structure. The dynamics of community formation is framed as a strategic game called community formation game: Given a social network, each node is selfish and selects communities to join or leave based on her own utility measurement. A community structure can be interpreted as an equilibrium of this game. We formulate the agents’ utility by the combination of a gain function and a loss function. Each agent can select multiple communities, which naturally captures the concept of “overlapping communities”. We propose a gain function based on Newman’s modularity function and a simple loss function that reflects the intrinsic costs incurred when people join the communities. We conduct extensive experiments under this framework; our results show that our algorithm is effective in identifying overlapping communities, and is often better than other algorithms we evaluated especially when many people belong to multiple communities.
@inproceedings{ijcai2011p429,
title = {Community Detection in Social Networks through Community Formation Games},
author = {Chen, Wei and Liu, Zhenming and Sun, Xiaorui and Wang, Yajun},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {2576--2580},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-429},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-429},
}
TY - CPAPER TI - Community Detection in Social Networks through Community Formation Games AU - Chen, Wei AU - Liu, Zhenming AU - Sun, Xiaorui AU - Wang, Yajun T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 2576 EP - 2580 DO - 10.5591/978-1-57735-516-8/IJCAI11-429 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-429 ER -Copied
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