Identifying influential nodes in weighted networks based on evidence theory

Daijun Wei, Xinyang Deng, Xiaoge Zhang, Yong Deng and Sankaran Mahadevan

Physica A: Statistical Mechanics and its Applications, 2013, vol. 392, issue 10, 2564-2575

Abstract: The design of an effective ranking method to identify influential nodes is an important problem in the study of complex networks. In this paper, a new centrality measure is proposed based on the Dempster–Shafer evidence theory. The proposed measure trades off between the degree and strength of every node in a weighted network. The influences of both the degree and the strength of each node are represented by basic probability assignment (BPA). The proposed centrality measure is determined by the combination of these BPAs. Numerical examples are used to illustrate the effectiveness of the proposed method.

Keywords: Complex networks; Influential nodes; Weighted network; Dempster–Shafer theory of evidence (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (35)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:392:y:2013:i:10:p:2564-2575

DOI: 10.1016/j.physa.2013.01.054

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