Abstract
Abstract
Identifying the influential nodes in a network is essential for network dynamic analysis. In this letter, inspired by the gravity model, we present an improved gravity model (EDGM) to identify the influential nodes in the network through the effective distance. Firstly, we calculate the degree of nodes. Then we construct the effective distance combined with the interaction frequency between nodes, so as to establish the effective distance gravity model. Comparing with the susceptible-infected model, the results show that Kendall's τ correlation coefficient of the EDGM could be enhanced by 2.36% for the gravity model. Compared with other methods, Kendall's τ correlation coefficient of the EDGM could be enhanced by 11.55%, 17.29%, 7.17% and 10.00% for the degree centrality, betweenness centrality, eigenvector centrality, and PageRank, respectively. The results show that the improved gravity model could effectively identify the influential nodes in the network.
Funder
National Natural Science Foundation of China
Subject
General Physics and Astronomy
Cited by
4 articles.
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