Dynamical Influence of Nodes Revisited: A Markov Chain Analysis of Epidemic Process on Networks

作     者：LI Ping ZHANG Jie XU Xiao-Ke SMALL Michael 李平;张捷;许小可;SMALL Michael

作者机构：Center for Networked SystemsSchool of Computer ScienceSouthwest Petroleum UniversityChengdu 610500 State Key Laboratory of Oil and Gas Reservoir Geology and ExploitationSouthwest Petroleum UniversityChengdu 610500 Center for Computational Systems BiologyFudan UniversityShanghai 200433 Hong Kong Polytechnic UniversityHung HomKowloonHong Kong School of Communication and Electronic EngineeringQingdao Technological UniversityQingdao 2665206 School of Mathematics and StatisticsUniversity of Western AustraliaCrawleyWA 6009Australia 

出 版 物：《Chinese Physics Letters》 (中国物理快报（英文版）)

年 卷 期：2012年第29卷第4期

页      面：248-251页

核心收录：

学科分类：07[理学] 070202[理学-粒子物理与原子核物理] 0702[理学-物理学] 

基　　金：Supported by the National Natural Science Foundation of China under Grant Nos 61104224,61004104 and 61104143 the PolyU Postdoctoral Fellowships Scheme(G-YX4A) the Research Grants Council of Hong Kong(BQ19H) 

主　　题：process dynamical eigenvector 

摘      要：We provide a theoretical analysis of node importance from the perspective of dynamical processes on *** particular,using Markov chain analysis of the susceptible-infected-susceptible (SIS) epidemic model on networks,we derive the node importance in terms of dynamical behaviors on network in a theoretical *** is found that this quantity happens to be the eigenvector centrality under some conditions,which bridges the topological centrality measure of the nodes with the dynamical influence of the nodes for the dynamical *** furthermore discuss the condition under which the eigenvector centrality is valid for dynamical phenomena on networks.