IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v389y2010i24p5832-5837.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437110007521
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2010.08.049?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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).
    3. 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).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:389:y:2010:i:24:p:5832-5837. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.