Community Detection in Complex Networks

With the rapidly growingevidence that various systems in nature and society can be modeledas complex networks, community detection in networks becomes a hotresearch topic in physics, sociology, computer society, etc.Although this investigation of community structures has motivatedmany diverse algorithms, most of them are unsuitable when dealingwith large networks due to their computational cost. In this paper,we present a faster algorithm ComTector, which is moreefficient for the community detection in large complex networksbased on the nature of overlapping cliques. This algorithm does notrequire any priori knowledge about the number or the originaldivision of the communities. With respect to practical applications,ComTector is challenging with five different types of networksincluding the classic Zachary Karate Club, ScientificCollaboration Network, South Florida Free Word AssociationNetwork, Urban Traffic Network, North America PowerGrid and the Telecommunication Call Network. Experimentalresults show that our algorithm can discover meaningful communitiesthat meet both the objective basis and our intuitions.