Efficient algorithm based on neighborhood overlap for community identification in complex networks

Kun Li, Xiaofeng Gong, Shuguang Guan and C.-H. Lai

Physica A: Statistical Mechanics and its Applications, 2012, vol. 391, issue 4, 1788-1796

Abstract: Community structure is an important feature in many real-world networks. Many methods and algorithms for identifying communities have been proposed and have attracted great attention in recent years. In this paper, we present a new approach for discovering the community structure in networks. The novelty is that the algorithm uses the strength of the ties for sorting out nodes into communities. More specifically, we use the principle of weak ties hypothesis to determine to what community the node belongs. The advantages of this method are its simplicity, accuracy, and low computational cost. We demonstrate the effectiveness and efficiency of our algorithm both on real-world networks and on benchmark graphs. We also show that the distribution of link strength can give a general view of the basic structure information of graphs.

Keywords: Complex networks; Community identification; Weak ties (search for similar items in EconPapers)
Date: 2012
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:391:y:2012:i:4:p:1788-1796

DOI: 10.1016/j.physa.2011.09.027

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