Community Detection Techniques for Evolving Social Networks

Social network (SN) can be defined as a set of entities and relationships among the entities. Social networks play a key role in the diffusion of information. The analysis of social networks has attracted many researchers in the field of social networking. This area of research has many challenges. This paper provides a survey on a social network and proposes a detailed classification of community detection algorithms along with examples based on graph properties. Community detection can be used in detecting a similar area of research interest in citation networks, detecting a like-minded customer in marketing recommendation systems, detection of interaction in protein networks etc. One of the main applications in social networking is analyzing detected communities. The detected communities in a social network are useful for understanding hidden patterns of a social network. The classification analyzed in this paper can play a vital role in analyzing and evaluating the community detection algorithms in different domains of applications.