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Identifying influential nodes in weighted networks based on evidence theory

Author

Listed:
  • Wei, Daijun
  • Deng, Xinyang
  • Zhang, Xiaoge
  • Deng, Yong
  • Mahadevan, Sankaran

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.

Suggested Citation

  • Wei, Daijun & Deng, Xinyang & Zhang, Xiaoge & Deng, Yong & Mahadevan, Sankaran, 2013. "Identifying influential nodes in weighted networks based on evidence theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2564-2575.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:10:p:2564-2575
    DOI: 10.1016/j.physa.2013.01.054
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    References listed on IDEAS

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