Review of Parallel and Distributed Community Detection Algorithms

Community detection is an important part of the analysis of the social networks. In the present era of digital world, online communication, content sharing, and maintaining contacts are mostly happening through online social networks. These networks are ever increasing and they are becoming very complex to analyze information. The traditional techniques which are available for community detection in social networks are not able to process this large-scale social networks data in efficient manner. This brings an essential and efficient ways to find large social network communities. In this paper, we review different algorithms available in the literature to find communities in large-scale community detection. In addition, we also discuss about various types computing frameworks available to process community detection algorithms in parallel like GraphX, Map reduce.