Greedy local algorithm for overlapping community detection in online social networks

Due to rapid growth of Social Networking Sites, a significant number of people interact with each other without any barriers of geographical distances or language. This communication among people is selective in the sense that they communicate only with likeminded people, and people of similar interests. This selective communication creates a typical structure in the networks which is known as community. Community structure is a significant property of social networks and hence its detection of prime importance in social network analysis and research. This paper presents Greedy Local Algorithm (GLA) for detecting overlaps between communities in social networks, which can detect dense overlaps between communities and results in lesser number of outliers.