Community detection in dynamic social networks: A game-theoretic approach

Hamidreza Alvari, Alireza Hajibagheri, Gita Sukthankar
2014 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)  
Most real-world social networks are inherently dynamic and composed of communities that are constantly changing in membership. As a result, recent years have witnessed increased attention toward the challenging problem of detecting evolving communities. This paper presents a gametheoretic approach for community detection in dynamic social networks in which each node is treated as a rational agent who periodically chooses from a set of predefined actions in order to maximize its utility
more » ... The community structure of a snapshot emerges after the game reaches Nash equilibrium; the partitions and agent information are then transferred to the next snapshot. An evaluation of our method on two real world dynamic datasets (AS-Internet Routers Graph and AS-Oregon Graph) demonstrates that we are able to report more stable and accurate communities over time compared to the benchmark methods.
doi:10.1109/asonam.2014.6921567 dblp:conf/asunam/AlvariHS14 fatcat:orshkdrdtrcbxjpsy76s4mje2m