A New Evaluation Method of Node Importance in Directed Weighted Complex Networks

Wang Yu (), Guo Jinli () and Liu Han
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Wang Yu: School of Management, University of Shanghai for Science and Technology, Shanghai200093, China
Guo Jinli: School of Management, University of Shanghai for Science and Technology, Shanghai200093, China
Liu Han: Trade and Technology Department, Xijing University, Xi’an710123, China

Journal of Systems Science and Information, 2017, vol. 5, issue 4, 367-375

Abstract: Current researches on node importance evaluation mainly focus on undirected and unweighted networks, which fail to reflect the real world in a comprehensive and objective way. Based on directed weighted complex network models, the paper introduces the concept of in-weight intensity of nodes and thereby presents a new method to identify key nodes by using an importance evaluation matrix. The method not only considers the direction and weight of edges, but also takes into account the position importance of nodes and the importance contributions of adjacent nodes. Finally, the paper applies the algorithm to a microblog-forwarding network composed of 34 users, then compares the evaluation results with traditional methods. The experiment shows that the method proposed can effectively evaluate the node importance in directed weighted networks.

Keywords: directed weighted complex network; node importance; in-weight intensity; importance contribution (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:5:y:2017:i:4:p:367-375:n:7

DOI: 10.21078/JSSI-2017-367-09

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