Ranking the spreading influence in complex networks

被引：249

作者：

Liu, Jian-Guo ^{[1
]}

Ren, Zhuo-Ming ^{[1
]}

Guo, Qiang ^{[1
]}

机构：

[1] Univ Shanghai Sci & Technol, Res Ctr Complex Syst Sci, Shanghai 200093, Peoples R China

来源：

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2013年 / 392卷 / 18期

关键词：

Network science; Spreading influence; K-shell decomposition; EPIDEMICS; INTERNET;

D O I：

10.1016/j.physa.2013.04.037

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

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.

引用

页码：4154 / 4159

页数：6