文献类型：期刊文献

英文题名：Information spreading on mobile communication networks: A new model that incorporates human behaviors

作者：Ren, Fei[1,2,3];Li, Sai-Ping[4];Liu, Chuang[5]

机构：[1]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Sch Sci, Shanghai 200237, Peoples R China;[3]East China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China;[4]Acad Sinica, Inst Phys, Taipei 115, Taiwan;[5]Hangzhou Normal Univ, Res Ctr Complex Sci, Hangzhou 311121, Zhejiang, Peoples R China

年份：2017

卷号：469

起止页码：334

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

收录：;EI(收录号：20164903083312);WOS:【SCI-EXPANDED(收录号:WOS:000392793500033)】；

基金：We are grateful to Prof. Wei-Xing Zhou and Dr. Yogesh Virkar for helpful comments and suggestions. This work was partially supported by the National Natural Science Foundation (Nos. 11205057 and 11305043), Fok Ying Tong Education Foundation Grant 132013, and the Fundamental Research Funds for the Central Universities (2015).

语种：英文

外文关键词：Complex networks; Information spreading; Mobile phone data

摘要：Recently, there is a growing interest in the modeling and simulation based on real social networks among researchers in multi-disciplines. Using an empirical social network constructed from the calling records of a Chinese mobile service provider, we here propose a new model to simulate the information spreading process. This model takes into account two important ingredients that exist in real human behaviors: information prevalence and preferential spreading. The fraction of informed nodes when the system reaches an asymptotically stable state is primarily determined by information prevalence, and the heterogeneity of link weights would slow down the information diffusion. Moreover, the sizes of blind clusters which consist of connected uninformed nodes show a power-law distribution, and these uninformed nodes correspond to a particular portion of nodes which are located at special positions in the network, namely at the edges of large clusters or inside the clusters connected through weak links. Since the simulations are performed on a real world network, the results should be useful in the understanding of the influences of social network structures and human behaviors on information propagation. (C) 2016 Elsevier B.V. All rights reserved.