Improved link entropy with dynamic community number detection for quantifying significance of edges in complex social networks

HIGHLIGHTS

  • who: Vasily Lubashevskiy and colleagues from the Institute for International Strategy, Tokyo International University, Matoba-kita, Kawagoe, Saitama, Japan have published the article: Improved Link Entropy with Dynamic Community Number Detection for Quantifying Significance of Edges in Complex Social Networks, in the Journal: Entropy 2023, 25, 365. of /2023/
  • what: The authors study the problem of quantifying the significance of edges in a complex network and propose a significantly version of the Entropy method. Running experiments on various benchmark networks the authors show that the proposed method outperforms the Entropy method in quantifying edge significance . . .

     

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