Analysis and Modeling for Competitive Diffusion of Multiple Topics in Online Social Networks

被引：0
作者：
Zhou Y. [1 ]
Liu L. [1 ]
Zhang B. [2 ]
Lei L. [3 ]
机构：
[1] Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an
[2] School of Computer Science and Engineering, Xi'an University of Technology, Xi'an
[3] Institute of Water Resources and Hydro-Electric Engineering, Xi'an University of Technology, Xi'an
来源：
Zhang, Beibei | 2017年 / Xi'an Jiaotong University卷 / 51期
关键词：
Diffusion model; Hot topics; Online social network; User behavior analysis;
D O I：
10.7652/xjtuxb201702001
中图分类号：
学科分类号：
摘要：
Competitive diffusion processes are analyzed, and a model for the competitive diffusion of multiple topics is proposed to understand the competitive diffusion of multiple topics in online social networks. Analyzing real network data, it is found that just a few users continue to focus on the same topic, and many users transfer their attentions among multiple similar topics. In this case, similar topics attract users to participate in a competitive situation. Based on the analysis results, a diffusion model describing the dynamic diffusion process of multiple topics in the competitive situation is proposed. Experiment validates that the model reproduces the unimodality and long tail characteristics of dynamic changes of users who participate in multiple topics, and achieves a good performance. A comparison with actual data show that the error of average peak time of the proposed model is 0.2 day, the error of average diffusion period is 2.4 days, and the error of average transferring proportion among topics is 1.2%. These results show that the model can effectively describe the competitive diffusion of multiple topics in online social networks. © 2017, Editorial Office of Journal of Xi'an Jiaotong University. All right reserved.
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页码：1 / 5and39
页数：538
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