文献类型：期刊文献

英文题名：Effects of attachment preferences on coevolution of opinions and networks

作者：Zhong, Li-Xin[1];Ren, Fei[2];Qiu, Tian[3];Xu, Jiang-Rong[1];Chen, Bi-Hui[1];Liu, Cai-Feng[1]

机构：[1]Hangzhou Dianzi Univ, Coll Sci, Hangzhou 310018, Peoples R China;[2]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[3]Nanchang Hangkong Univ, Sch Informat Engn, Nanchang 330063, Peoples R China

年份：2010

卷号：389

期号：13

起止页码：2557

外文期刊名：PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

收录：;EI(收录号：20101612861803);WOS:【SCI-EXPANDED(收录号:WOS:000277824800009)】；

基金：This work is the research fruit of Zhejiang Social Sciences Association under Grant 08N51, "Chen Guang" project supported by Shanghai Municipal Education Commission and Shanghai Education Development Foundation (2008CG37), the Natural Science Foundation of Zhejiang Province under Grant KYS011507034, and the National Natural Science Foundation of China (Grant Nos. 10905023, 10805025, and 10774080).

语种：英文

外文关键词：Coevolving networks; Opinion formation; Personal preference

摘要：In the coevolution of network structures and opinion formation, we investigate the effects of a mixed population with distinctive relinking preferences on both the convergence time and the network structures. It has been found that a heterogeneous network structure is easier to be reached with more high-degree-preferential (HOP) nodes. There exists high correlation between the convergence time and the network heterogeneity. The heterogeneous degree distribution caused by preferential attachment accelerates the convergence to a consensus state and the shortened convergence time inhibits the occurrence of the following disquieting situation that occurs in a continuously evolving network: with preferential attachment and long-time evolvement, most of the nodes would become separated and only a few leaders would have immediate neighbors. Analytical calculations based on mean field theory reveal that both the transition point p(tr) and the consensus time tau depend upon the standard deviation of the degree distribution sigma(d). p(tr) increases while tau decreases with the rise of sigma(d). Functions of p(tr) = < k >/(< k > + 1) and tau = a(N)K/(sigma(2)(d) - K) are found. Theoretical analyses are in accordance with simulation data. (C) 2010 Elsevier B.V. All rights reserved.