Community detection using local neighborhood in complex networks
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Date
2015
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
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.
Description
Abstract. Full text article available at https://doi.org/10.1016/j.physa.2015.05.044
Keywords
Complex networks, Local neighborhood, Neighborhood ratio, Community detection algorithms, Local community neighborhood, Data mining, Behavior science, Community structure, Algorithms
Citation
Eustace, J., Wang, X., & Cui, Y. (2015). Community detection using local neighborhood in complex networks. Physica A: Statistical Mechanics and its Applications, 436, 665-677.