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Human comment dynamics in on-line social systems

Author

Listed:
  • Wu, Ye
  • Zhou, Changsong
  • Chen, Maoying
  • Xiao, Jinghua
  • Kurths, Jürgen

Abstract

Human comment is studied using data from ‘tianya’ which is one of the most popular on-line social systems in China. We found that the time interval between two consecutive comments on the same topic, called inter-event time, follows a power-law distribution. This result shows that there is no characteristic decay time on a topic. It allows for very long periods without comments that separate bursts of intensive comments. Furthermore, the frequency of a different ID commenting on a topic also follows a power-law distribution. It indicates that there are some “hubs” in the topic who lead the direction of the public opinion. Based on the personal comments habit, a model is introduced to explain these phenomena. The numerical simulations of the model fit well with the empirical results. Our findings are helpful for discovering regular patterns of human behavior in on-line society and the evolution of the public opinion on the virtual as well as real society.

Suggested Citation

  • Wu, Ye & Zhou, Changsong & Chen, Maoying & Xiao, Jinghua & Kurths, Jürgen, 2010. "Human comment dynamics in on-line social systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5832-5837.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:24:p:5832-5837
    DOI: 10.1016/j.physa.2010.08.049
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    Cited by:

    1. Rashidisabet, Homa & Ajilore, Olusola & Leow, Alex & Demos, Alexander P., 2022. "Revisiting power-law estimation with applications to real-world human typing dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    2. Jie Zhao & Jianfei Wang & Suping Fang & Peiquan Jin, 2018. "Towards Sustainable Development of Online Communities in the Big Data Era: A Study of the Causes and Possible Consequence of Voting on User Reviews," Sustainability, MDPI, vol. 10(9), pages 1-18, September.
    3. Zhang, Sheng-Tai & Yuan, Hao-Yu & Duan, Ling-Li, 2020. "Analysis of human behavior statistics law based on WeChat Moment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).

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