<p>Due to the characteristics of node reuse and structure hole formation in two-layer integrated networks, a novel key node identification method for two-layer fusion networks inspired by improved structural holes. Firstly, the structure characteristics of node reuse in two-layer fusion networks are analyzed, and the node fusion coefficient is defined. Secondly, combined with the node fusion coefficient, the calculation method of the improved hole node centrality and network constraint coefficient is proposed. Finally, the key node identification algorithm flow and simulation experiments of two-layer fusion network based on enhanced structural holes are presented. Simulation results show that the proposed method improves the accuracy of key node identification in two-layer fusion networks and solves the problem that traditional key node identification methods cannot be directly applied to two-layer fusion networks.</p>

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Key node identification method for two-layer fusion networks based on improved structural holes

  • Bo Chen,
  • Yulin Zhang,
  • Yunming Wang,
  • Rui Tong,
  • Yufeng Chen,
  • Lingdong Sun,
  • Wenxue Xie

摘要

Due to the characteristics of node reuse and structure hole formation in two-layer integrated networks, a novel key node identification method for two-layer fusion networks inspired by improved structural holes. Firstly, the structure characteristics of node reuse in two-layer fusion networks are analyzed, and the node fusion coefficient is defined. Secondly, combined with the node fusion coefficient, the calculation method of the improved hole node centrality and network constraint coefficient is proposed. Finally, the key node identification algorithm flow and simulation experiments of two-layer fusion network based on enhanced structural holes are presented. Simulation results show that the proposed method improves the accuracy of key node identification in two-layer fusion networks and solves the problem that traditional key node identification methods cannot be directly applied to two-layer fusion networks.