Influence Model of User Behavior Characteristics on Information Dissemination

  • Shao Chun Han Beijing Jiao tong University Beijing, 100044, China
  • Yun Liu Beijing Jiao tong University Beijing, 100044, China
  • Hui Ling Chen 1. School of Pharmaceutical Science and Technology Tianjin University 2. TianJin University of Traditional Chinese Medicine
  • Zhen Jiang Zhang Beijing Jiao tong University Beijing, 100044, China


Quantitative analysis on human behavior, especially mining and modeling temporal and spatial regularities, is a common focus of statistical physics and complexity sciences. The in-depth understanding of human behavior helps in explaining many complex socioeconomic phenomena, and in finding applications in public opinion monitoring, disease control, transportation system design, calling center services, information recommendation. In this paper,we study the impact of human activity patterns on information diffusion. Using SIR propagation model and empirical data, conduct quantitative research on the impact of user behavior on information dissemination. It is found that when the exponent is small, user behavioral characteristics have features of many new dissemination nodes, fast information dissemination, but information continued propagation time is short, with limited influence; when the exponent is big, there are fewer new dissemination nodes, but will expand the scope of information dissemination and extend information dissemination duration; it is also found that for group behaviors, the power-law characteristic a greater impact on the speed of information dissemination than individual behaviors. This study provides a reference to better understand influence of social networking user behavior characteristics on information dissemination and kinetic effect.


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How to Cite
HAN, Shao Chun et al. Influence Model of User Behavior Characteristics on Information Dissemination. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 11, n. 2, p. 209-223, jan. 2016. ISSN 1841-9844. Available at: <>. Date accessed: 16 july 2020. doi:


SIR, behavior dynamics, scaling laws, information dissemination