A novel method to rank influential nodes in complex networks based on tsallis entropy

Xuegong Chen, Jie Zhou, Zhifang Liao*, Shengzong Liu*, Yan Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)
57 Downloads (Pure)

Abstract

With the rapid development of social networks, it has become extremely important to evaluate the propagation capabilities of the nodes in a network. Related research has wide applications, such as in network monitoring and rumor control. However, the current research on the propagation ability of network nodes is mostly based on the analysis of the degree of nodes. The method is simple, but the effectiveness needs to be improved. Based on this problem, this paper proposes a method that is based on Tsallis entropy to detect the propagation ability of network nodes. This method comprehensively considers the relationship between a node's Tsallis entropy and its neighbors, employs the Tsallis entropy method to construct the TsallisRank algorithm, and uses the SIR (Susceptible, Infectious, Recovered) model for verifying the correctness of the algorithm. The experimental results show that, in a real network, this method can effectively and accurately evaluate the propagation ability of network nodes.

Original languageEnglish
Article number848
Number of pages18
JournalEntropy
Volume22
Issue number8
Early online date31 Jul 2020
DOIs
Publication statusPublished - Aug 2020

Keywords

  • Influential nodes
  • SIR model
  • Tsallis entropy

ASJC Scopus subject areas

  • Information Systems
  • Mathematical Physics
  • Physics and Astronomy (miscellaneous)
  • Electrical and Electronic Engineering

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