Community Cores in Evolving Networks

Massoud Seifi and Jean-Loup Guillaume

Proceedings of the Mining Social Network Dynamic 2012 Workshop (MSND), Inconjunction with the international conference World Wide Web WWW 2012, Lyon,France, pp. 1173-1180

Community structure is a key property of complex networks.Many algorithms have been proposed to automatically detect communities in static networks but few studies haveconsidered the detection and tracking of communities in anevolving network. Tracking the evolution of a given community over time requires a clustering algorithm that producesstable clusters. However, most community detection algorithms are very unstable and therefore unusable for evolvingnetworks. In this paper, we apply the methodology proposedin [14] to detect what we call community cores in evolvingnetworks. We show that cores are much more stable than »classical » communities and that we can overcome the disadvantages of the stabilized methods.