Community detection in signed networks based on discrete-time model

doi:10.1088/1674-1056/26/1/018901

Abstract Community detection in signed networks has been studied widely in recent years. In this paper, a discrete difference equation is proposed to imitate the consistently changing phases of the nodes. During the interaction, each node will update its phase based on the difference equation. Each node has many different nodes connected with it, and these neighbors have different influences on it. The similarity between two nodes is applied to describe the influences between them. Nodes with high positive similarities will get together and nodes with negative similarities will be far away from each other. Communities are detected ultimately when the phases of the nodes are stable. Experiments on real world and synthetic signed networks show the efficiency of detection performance. Moreover, the presented method gains better detection performance than two existing good algorithms.

Keywords: community detection signed networks discrete-time model similarity

Received: 19 May 2016
Revised: 26 June 2016
Accepted manuscript online:

PACS:	89.75.Fb	(Structures and organization in complex systems)
	89.75.Hc	(Networks and genealogical trees)
	84.30.Bv	(Circuit theory)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 11261034, 71561020, 61503203, and 11326239), the Higher School Science and Technology Research Project of Inner Mongolia, China (Grant No. NJZY13119), and the Natural Science Foundation of Inner Mongolia, China (Grant Nos. 2015MS0103 and 2014BS0105).

Corresponding Authors: Jianrui Chen
E-mail: jianrui_chen@sina.com

Cite this article:

Jianrui Chen(陈建芮), Li Zhang(张莉), Weiwei Liu(刘维维), Zaizai Yan(闫在在) Community detection in signed networks based on discrete-time model 2017 Chin. Phys. B 26 018901

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