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Analyzing netizens’ view and reply behaviors on the forum

Author

Listed:
  • Yu, Jiefei
  • Hu, Yanqing
  • Yu, Min
  • Di, Zengru

Abstract

Quantitative understanding of human behaviors provides elementary comprehension of the complexity of social system. In this paper, the netizens’ behaviors on the Bulletin Board System (BBS) are investigated by the statistical analysis of views and replies on some forums. The statistical results show that the number of views and replies obeys the power-law distribution with different power exponents. In addition, when the distribution of both views and replies follows power-law distribution, they are found to have a nonlinear relationship. This relationship also obeys the power function, when transformed to the log–log plot, its fit curve appears as a straight line. Based on the estimation of slopes and intercepts of the lines, we can characterize the view and reply behaviors quantitatively. The results reveal that the Chinese and western netizens have different preferences when replying and viewing the threads. At last, the time series of reply behaviors are analyzed. All series show us with a high burstiness and low memory.

Suggested Citation

  • Yu, Jiefei & Hu, Yanqing & Yu, Min & Di, Zengru, 2010. "Analyzing netizens’ view and reply behaviors on the forum," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3267-3273.
  • Handle: RePEc:eee:phsmap:v:389:y:2010:i:16:p:3267-3273
    DOI: 10.1016/j.physa.2010.03.043
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    References listed on IDEAS

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    1. Li, Nan-Nan & Zhang, Ning & Zhou, Tao, 2008. "Empirical analysis on temporal statistics of human correspondence patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(25), pages 6391-6394.
    2. Johansen, Anders, 2004. "Probing human response times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 286-291.
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    Cited by:

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    2. Li, Zhenpeng & Tang, Xijin & Zhou, Haijun & Yan, Donghui, 2018. "An empirical investigation and theoretic modeling for the collective online visiting behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 969-980.
    3. Pan, Junshan & Liu, Ying & Liu, Xiang & Hu, Hanping, 2016. "Discriminating bot accounts based solely on temporal features of microblog behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 193-204.
    4. Yan, Qiang & Yi, Lanli & Wu, Lianren, 2012. "Human dynamic model co-driven by interest and social identity in the MicroBlog community," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1540-1545.

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