A benefit function for community detection based on edge and path of length two

Yaoyi Zhang, Qingyu Huang, Guohai Cao (), Mengwei Zhao (), Siyuan Zhang () and Yabo Wu ()
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Yaoyi Zhang: Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu 610213, P. R. China
Qingyu Huang: Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu 610213, P. R. China
Guohai Cao: Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu 610213, P. R. China
Mengwei Zhao: Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu 610213, P. R. China
Siyuan Zhang: Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu 610213, P. R. China
Yabo Wu: Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu 610213, P. R. China

International Journal of Modern Physics C (IJMPC), 2021, vol. 32, issue 06, 1-9

Abstract: In the field of community detection in complex networks, the most commonly used approach to this problem is the maximization of the benefit function known as “modularity”. In this study, it is found that the path of length two have the similar property as the edge, which is denser within communities and sparser between different communities. In order to take both edge and path of length two into consideration simultaneously, a self-loop is added to each node of the network and a novel benefit function has been defined. To divide the network into two communities, a second eigenvector method is proposed based on maximization of our new benefit function. Experimental results obtained by applying the method to karate club network and dolphin social network show the feasibility of our benefit function and the effectiveness of our algorithm.

Keywords: Community detection; self-loop; path of length 2; benefit function (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1142/S0129183121500820

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