Community Detection in Social Networks Using Extended Self Organizing Map Algorithm

Social networks are often studied as graphs, and detecting communities in a social network can be modeled as a seriously non linear optimization problem. Soft computing techniques have shown promising results for solving this problem. In this paper, we have proposed a new approach based on self organizing map to community detection. By using a proper weight updating scheme, a network can be organized into dense sub graphs according to the topological connection of each node. A community is usually defined in a qualitative way, as a subset of nodes of a network which are more densely connected among them -selves than to the rest of the networks.