Local community finding using synthetic coordinates

Abstract

A fundamental problem in social networking and computing is the community finding problem that can be used in a lot of social networks' applications. In this paper, we propose an algorithm that finds the entire community structure of a network, based on interactions between neighboring nodes (distributed method) and on an unsupervised centralized clustering algorithm. Experimental results and comparisons with another method found in the literature are presented for a variety of benchmark graphs with known community structure, derived by varying a number of graph parameters. The experimental results demonstrate the high performance of the proposed algorithm to detect communities. © 2011 Springer-Verlag.