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Individual popularity and activity in online social systems

Author

Listed:
  • Hu, Haibo
  • Han, Dingyi
  • Wang, Xiaofan

Abstract

We propose a stochastic model of web user behaviors in online social systems, and study the influence of the attraction kernel on the statistical property of user or item occurrence. Combining the different growth patterns of new entities and attraction patterns of old ones, different heavy-tailed distributions for popularity and activity which have been observed in real life, can be obtained. From a broader perspective, we explore the underlying principle governing the statistical feature of individual popularity and activity in online social systems and point out the potential simple mechanism underlying the complex dynamics of the systems.

Suggested Citation

  • Hu, Haibo & Han, Dingyi & Wang, Xiaofan, 2010. "Individual popularity and activity in online social systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(5), pages 1065-1070.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:5:p:1065-1070
    DOI: 10.1016/j.physa.2009.11.007
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    Citations

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    Cited by:

    1. Fan, Rui & Xu, Ke & Zhao, Jichang, 2018. "An agent-based model for emotion contagion and competition in online social media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 245-259.
    2. Bing Wu & Shan Jiang & Hsinchun Chen, 2015. "The impact of individual attributes on knowledge diffusion in web forums," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(6), pages 2221-2236, November.
    3. Sun, Xin & Dong, Junyu & Tang, Ruichun & Xu, Mantao & Qi, Lin & Cai, Yang, 2015. "Topological evolution of virtual social networks by modeling social activities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 259-267.

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