Partition Clustering-Based Method for Detecting Community Structures in Weighted Social Networks

Abstract

Community identification is one of the most broadly studied topics in social network analysis nowadays. Community detection finds its applications in almost any scientific direction. Despite of the fact that many works are dedicated to finding communities in social networks, this problem still not solved satisfactorily. This is due to the complexity and size of real world networks. In this paper, we propose a new approach for finding community structure in social networks derived from information available on the Web. We shall start with brief introduction of social networking concepts. Then, state of the art of social networks on the Web will be followed by the detailed method description and experimental result.