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Heterogeneous characters modeling of instant message services users’ online behavior

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
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