Using mapping entropy to identify node centrality in complex networks

Tingyuan Nie, Zheng Guo, Kun Zhao and Zhe-Ming Lu

Physica A: Statistical Mechanics and its Applications, 2016, vol. 453, issue C, 290-297

Abstract: The problem of finding the best strategy to attack a network or immunize a population with a minimal number of nodes has attracted much current research interest. The assessment of node importance has been a fundamental issue in the research of complex networks. In this paper, we propose a new concept called mapping entropy (ME) to identify the importance of a node in the complex network. The concept is established according to the local information which considers the correlation among all neighbors of a node. We evaluate the efficiency of the centrality by static and dynamic attacks on standard network models and real-world networks. The simulation result shows that the new centrality is more efficient than traditional attack strategies, whether it is static or dynamic.

Keywords: Mapping entropy; Centrality; Complex network; Invulnerability (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:453:y:2016:i:c:p:290-297

DOI: 10.1016/j.physa.2016.02.009

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