Community detection using local neighborhood in complex networks

Justine Eustace, Xingyuan Wang and Yaozu Cui

Physica A: Statistical Mechanics and its Applications, 2015, vol. 436, issue C, 665-677

Abstract: It is common to characterize community structure in complex networks using local neighborhood. Existing related methods fail to estimate the accurate number of nodes present in each community in the network. In this paper a community detection algorithm using local community neighborhood ratio function is proposed. The proposed algorithm predicts vertex association to a specific community using visited node overlapped neighbors. In the beginning, the algorithm detects local communities; then through iterations and local neighborhood ratio function, final communities are detected by merging close related local communities. Analysis of simulation results on real and artificial networks shows the proposed algorithm detects well defined communities in both networks by wide margin.

Keywords: Complex networks; Data mining; Community detection algorithms; Neighborhood ratio; Behavior science (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:436:y:2015:i:c:p:665-677

DOI: 10.1016/j.physa.2015.05.044

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