Email community detection using artificial ant colony clustering

Abstract

The investigation of community structures in networks is an important issue in many domains and disciplines. Several types of algorithms exist for revealing the community structure in networks. However, Most of these algorithms consider only structure of the network, ignoring some additional conditions such as direction, weight, semantic, etc. In this paper we consider the behaviors of each individuals and describe an ant colony clustering algorithm for automatically identifying social communities from email network. This algorithm is successfully tested and evaluated on the Enron email dataset of 517,431 emails from 151 users, and shows that the method is effective at identifying true communities, both formal and informal. © Springer-Verlag Berlin Heidelberg 2007.