Method of analyzing the influence of network structure on information diffusion

被引:18
|
作者
Nagata, Katsuya [1 ]
Shirayama, Susumu [1 ]
机构
[1] Univ Tokyo, Sch Engn, Dept Syst Innovat, Bunkyo Ku, Tokyo 1138656, Japan
关键词
Information diffusion; Complex network; Network structure; Data mining;
D O I
10.1016/j.physa.2012.02.031
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Social phenomena are affected by the structure of networks consisting of personal relationships. In the present paper, the diffusion of information among people is examined. In particular, the relationship between the network structure and the dynamics is studied. First, several networks are generated using the proposed network model and other network models, such as the WS model and the KE model. By changing the parameters of the network models, networks with different structures are generated. The parameters of the network models determine the topology of the networks and the statistical indicators. Second, the role of network structure on information diffusion is investigated through numerical simulations using a simple information diffusion model of the networks. Two data mining methods are used to analyze the results. A neural network predicts the convergence rate and the time using six explanatory variables, and a decision tree reveals the statistical indicator that has a strong effect on the information diffusion. After these analyses, important statistical variables explaining the information diffusion are shown. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:3783 / 3791
页数:9
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