期刊
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
卷 392, 期 18, 页码 4154-4159出版社
ELSEVIER
DOI: 10.1016/j.physa.2013.04.037
关键词
Network science; Spreading influence; K-shell decomposition
资金
- NSFC [91024026, 71071098, 71171136]
- Innovation Program of Shanghai Municipal Education Commission [11ZZ135, 11YZ110]
- Shanghai Rising-Star Program [11QA1404500]
- Key Project of Chinese Ministry of Education [211057]
Identifying the node spreading influence in networks is an important task to optimally use the network structure and ensure the more efficient spreading in information. In this paper, by taking into account the shortest distance between a target node and the node set with the highest k-core value, we present an improved method to generate the ranking list to evaluate the node spreading influence. Comparing with the epidemic process results for four real networks and the Barabasi-Albert network, the parameterless method could identify the node spreading influence more accurately than the ones generated by the degree k, closeness centrality, k-shell and mixed degree decomposition methods. This work would be helpful for deeply understanding the node importance of a network. (C) 2013 Elsevier B.V. All rights reserved.
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