A Comparison of Overlapping Community Detection in Large Complex Network

Many large scale network contains community structure, that nodes are densely connected with own group and less connected to other groups. Community contains users those having similar characteristics from other groups or community. Now days, more number of people are paying attention on social network for information, news, comments, likes etc. Due to this social network sites generates large number of data. These issues often make social network data very complex to analyze manually. In network, there may be possibilities that one node may belongs to one or more than one groups that is called overlapping of nodes. Possibility of overlapping community is high in real world network. There are many fields in which community detection is necessary for example in politics, business, news, and social network like Facebook, Twitter, and LinkedIn etc. In social network large number of overlapping community is available, for analysis of this type of communities or groups in network is tedious task. Therefore research work is based on a heuristic approach to discover overlapped community in large complex network.