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| Method for Identifying Critical Nodes Based on Closed Triangle Motifs |
| XU Yue, LIU Xueming
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| School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China |
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Abstract Critical nodes in complex networks can influence the system functionality. Many real networks have a significant number of closed triangle motifs. To explore the influence of these motifs on the importance of nodes, a critical nodes identification method based on closed triangle motifs is proposed. The algorithm measures the importance of each motif and evaluates the node importance through the motif weights and node degrees. Robustness experiments and propagation experiments based on the SIR model are carried out with six real networks. The experimental results show that this method can identify critical nodes of the network more effectively than the DC method, K-shell method, WL method, and ME method.
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Received: 22 January 2022
Published: 28 December 2023
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