An efficient agent-based algorithm for overlapping community detection using nodes' closeness

Communities are groups of nodes forming tightly connected units in networks. Some nodes can be shared between different communities of a network. The presence of overlapping nodes and their associated membership diversity is a common characteristic of social networks. Analyzing these overlapping structures can reveal valuable information about the intrinsic features of realistic complex networks, especially social networks. In this paper, we propose a novel algorithm that is able to detect overlapping and non-overlapping community structures in complex networks. This algorithm uses a number of agents for investigation of the input network. These agents consider different nodes' closeness in their investigations. Various experiments are carried out on both synthetic and real-world networks that prove that the proposed algorithm outperforms most state-of-the-art algorithms of this field both in terms of the accuracy and execution time. (C) 2013 Elsevier B.V. All rights reserved.