Detecting community structure in complex networks via resistance distance

Teng Zhang and Changjiang Bu

Physica A: Statistical Mechanics and its Applications, 2019, vol. 526, issue C

Abstract: For two vertices i and j in a connected network G, the resistance distance between i and j is defined to be the effective resistance between them when unit resistors are placed on every edge of G. In this paper, by utilizing Gaussian function of the resistance distance between two vertices associated with each edge, the original network G is converted into weighted network G′. Next, applying the bisection spectral method, the G′ is divided into two subnetworks. And repeat this process in the subnetwork, the community structure of G is detected. Three real-world networks are used to test the proposed method. Experimental results demonstrate the feasibility and effectiveness by the proposed method in comparison with other community discovery methods.

Keywords: Resistance distance; Spectral partitioning; Laplacian matrix; Community structure (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119303826

DOI: 10.1016/j.physa.2019.04.018

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