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Based on Agent Model and -Core Decomposition to Analyze the Diffusion of Mass Incident in Microblog

Author

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  • Jun Pan
  • Huizhang Shen
  • Zhong Chen

Abstract

Mass incidents, which may influence the stability and security of the society in China, are getting more and more attentions not only from policy makers but also from Chinese social researchers. Catching the diffusion mechanism is believed to be critical to understand essential of these mass incidents since message dissemination plays important roles in every stage of mass incident. Recently, online social networks including Weibo (Chinese Twitter) become more and more popular in China. There are reports showing that Weibo discussion has accompanied the processes of most mass incidents happening in China in these few years. So, in this paper, we aim at introducing -Core decomposition method from complex network to the analysis on how to manage the diffusion of mass incident in Weibo based on agent based model which can simulate Weibo user’s actions when mass incident happens. This work can help people understand how mass incident messages spread across the network. And then, people may have better strategy to manage the diffusion of mass incidents.

Suggested Citation

  • Jun Pan & Huizhang Shen & Zhong Chen, 2017. "Based on Agent Model and -Core Decomposition to Analyze the Diffusion of Mass Incident in Microblog," Complexity, Hindawi, vol. 2017, pages 1-10, December.
  • Handle: RePEc:hin:complx:6416795
    DOI: 10.1155/2017/6416795
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    References listed on IDEAS

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    1. Rand, William & Rust, Roland T., 2011. "Agent-based modeling in marketing: Guidelines for rigor," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 181-193.
    2. Dominey, M. J. G. & Hill, R. M., 2004. "Performance of approximations for compound Poisson distributed demand in the newsboy problem," International Journal of Production Economics, Elsevier, vol. 92(2), pages 145-155, November.
    3. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 441-458, May.
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