Detecting Link Communities Based on Local Information in Social Networks

Recent years have seen the development of online social networks.Many algorithms have been proposed that are able to assign each node to more than a single community.The traditional approaches were always focusing on the node community,while some recent studies have shown great advantage of link community approach which partitions links instead of nodes into communities.In this paper,we present a novel algorithm LLCM(local link community mining algorithm) for discovering link communities in networks.A local link community can be detected by maximizing a local link fitness function from a seed link,which was ranked previously.The proposed LLCM algorithm has been tested on both synthetic and real world networks,and it has been compared with other link community detecting algorithms.The experimental results showed LLCM achieves significant improvement on link community structure.