CPR-TOPSIS: a novel algorithm for finding influential nodes in complex networks based on communication probability and relative entropy

DOI10.1016/j.physa.2022.127797OpenAlexW4283277456WikidataQ113866898 ScholiaQ113866898MaRDI QIDQ2162956

Chen Dong, Lei Meng, Pingle Yang, Gui-Qiong Xu

Publication date: 9 August 2022

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physa.2022.127797

zbMATH Keywords

relative entropycomplex networksTOPSISinfluential nodescommunication probability

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Uses Software

• InfGCN

Cites Work

• Identifying influential spreaders in complex networks based on gravity formula
• A new measure of identifying influential nodes: efficiency centrality
• A generalized gravity model for influential spreaders identification in complex networks
• Measure the structure similarity of nodes in complex networks based on relative entropy
• A novel method to evaluate node importance in complex networks
• Identifying node importance based on evidence theory in complex networks
• A new status index derived from sociometric analysis
• GPN: A novel gravity model based on position and neighborhood to identify influential nodes in complex networks
• Collective dynamics of ‘small-world’ networks

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