An Analysis of Overlapping Community Detection Algorithms in Social Networks

Abstract

In the field of research, Social Network Analysis is prevalent domain which pulls the attention of many data mining experts. Social network analysis is the specific field of sociology and anthropology. It shares a number of characteristics common to real network. Some real networks like Facebook, Twitter exhibit the concept of community structure within the network. Social network is represented as a network graph. Detecting the communities involves finding the densely connected nodes. Overlapping communities are possible if a node is a member of more than one community. This paper discusses various modularity based approaches on detecting the overlapping communities in the social networks. This work aims in providing the characteristics and limitations of modularity based overlapping community detection algorithms.