Identifying influential nodes in complex networks based on expansion factor

被引：9

作者：

Liu, Dong ^{[1
,2
]}

Jing, Yun ^{[1
]}

Chang, Baofang ^{[1
]}

机构：

[1] Henan Normal Univ, Sch Comp & Informat Engn, Xinxiang 453007, Peoples R China

[2] Engn Technol Res Ctr Comp Intelligence & Data Min, Xinxiang 453007, Henan Province, Peoples R China

来源：

INTERNATIONAL JOURNAL OF MODERN PHYSICS C | 2016年 / 27卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Influential spreaders; centrality; expansion contribution; complex networks; CENTRALITY; SPREADERS; INTERNET; RANKING;

D O I：

10.1142/S0129183116501059

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Identifying the top influential spreaders in a network has practical significance. In this paper, we propose a novel centrality to identify influential spreaders based on expansion factor. Nodes with high expansion factor centrality (EFC) have strong spreading capability. During the course of the work, an improved strategy is proposed to reduce the time complexity of EFC. We discuss the correlations between EFC and the other five classical indicators. Simulation results on the Susceptible-Infected-Removed (SIR) model manifest that EFC can identify influential nodes and find some critical influential nodes neglected by other indicators.

引用

页数：16

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