A dynamic algorithm for community detection in social networks

Social networks can be modeled by graphs with nodes and edges, and communities are sub graphs within networks. This paper proposes a new dynamic algorithm based on the modularity given by Newman and Girvan (NG modularity for short). Further more, this paper applies the proposed algorithm to real network data. The experimental results show that our algorithm can dynamically detect communities in a network, and the communities detected with the algorithm fits better with the real communities.