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Identifying influential nodes in complex networks based on closeness energy

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  • Wang, Jinping
  • Sun, Shaowei

Abstract

Identifying influential nodes in complex network is crucial for understanding the network’s structure and maintaining its stability. In recent years, scholars have designed methods for identifying influential nodes from the perspective of graph energy. However, analysis shows that the method based on distance Laplacian energy is limited by network connectivity. To address the above weaknesses, we propose closeness energy centrality (CEC), which uses the closeness energy of the network before and after node deletion as an evaluation metric. By introducing the closeness matrix, the CEC method expands the applicability of the network. By comparing it with eight traditional methods in four aspects, we verify that the CEC method’s performance is significantly better than that of other methods.

Suggested Citation

  • Wang, Jinping & Sun, Shaowei, 2025. "Identifying influential nodes in complex networks based on closeness energy," Chaos, Solitons & Fractals, Elsevier, vol. 200(P2).
    • Handle: RePEc:eee:chsofr:v:200:y:2025:i:p2:s0960077925010902
    DOI: 10.1016/j.chaos.2025.117077
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