IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0195518.html
   My bibliography  Save this article

Heterogeneous characters modeling of instant message services users’ online behavior

Author

Listed:
  • Hongyan Cui
  • Ruibing Li
  • Yajun Fang
  • Berthold Horn
  • Roy E Welsch

Abstract

Research on temporal characteristics of human dynamics has attracted much attentions for its contribution to various areas such as communication, medical treatment, finance, etc. Existing studies show that the time intervals between two consecutive events present different non-Poisson characteristics, such as power-law, Pareto, bimodal distribution of power-law, exponential distribution, piecewise power-law, et al. With the occurrences of new services, new types of distributions may arise. In this paper, we study the distributions of the time intervals between two consecutive visits to QQ and WeChat service, the top two popular instant messaging services in China, and present a new finding that when the value of statistical unit T is set to 0.001s, the inter-event time distribution follows a piecewise distribution of exponential and power-law, indicating the heterogeneous character of IM services users’ online behavior in different time scales. We infer that the heterogeneous character is related to the communication mechanism of IM and the habits of users. Then we develop a combination model of exponential model and interest model to characterize the heterogeneity. Furthermore, we find that the exponent of the inter-event time distribution of the same service is different in two cities, which is correlated with the popularity of the services. Our research is useful for the application of information diffusion, prediction of economic development of cities, and so on.

Suggested Citation

  • Hongyan Cui & Ruibing Li & Yajun Fang & Berthold Horn & Roy E Welsch, 2018. "Heterogeneous characters modeling of instant message services users’ online behavior," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-21, May.
    • Handle: RePEc:plo:pone00:0195518
    DOI: 10.1371/journal.pone.0195518
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0195518
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0195518&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0195518?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
    ---><---

    References listed on IDEAS

    as
    1. Yerali Gandica & João Carvalho & Fernando Sampaio dos Aidos & Renaud Lambiotte & Timoteo Carletti, 2017. "Stationarity of the inter-event power-law distributions," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-10, March.
    2. Jinhong Kim & Deokjae Lee & Byungnam Kahng, 2013. "Microscopic Modelling Circadian and Bursty Pattern of Human Activities," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-7, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Jian-Guo & Li, Ren-De & Guo, Qiang & Zhang, Yi-Cheng, 2018. "Collective iteration behavior for online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 490-497.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0195518. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.