中国物理B ›› 2020, Vol. 29 ›› Issue (5): 58901-058901.doi: 10.1088/1674-1056/ab81fe

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇    

Asynchronism of the spreading dynamics underlying the bursty pattern

Tong Wang(王童), Ming-Yang Zhou(周明洋), Zhong-Qian Fu(付忠谦)   

  1. 1 Department of Electronic Science and Technology, University of Science and Technology of China, Hefei 230027, China;
    2 Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China;
    3 Department of Physics, University of Fribourg, Chemin du Musée 3, Fribourg, CH-1700, Switzerland
  • 收稿日期:2019-04-15 出版日期:2020-05-05 发布日期:2020-05-05
  • 通讯作者: Ming-Yang Zhou E-mail:zhoumy2010@gmail.com
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 61703281, 11547040, 61803266, 61503140, and 61873171), the PhD Start-Up Fund of Natural Science Foundation of Guangdong Province, China (Grant Nos. 2017A030310374 and 2016A030313036), the Science and Technology Innovation Commission of Shenzhen, China (Grant No. JCYJ20180305124628810), and the China Scholarship Council (Grant No. 201806340213).

Asynchronism of the spreading dynamics underlying the bursty pattern

Tong Wang(王童)1,3, Ming-Yang Zhou(周明洋)2, Zhong-Qian Fu(付忠谦)1   

  1. 1 Department of Electronic Science and Technology, University of Science and Technology of China, Hefei 230027, China;
    2 Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China;
    3 Department of Physics, University of Fribourg, Chemin du Musée 3, Fribourg, CH-1700, Switzerland
  • Received:2019-04-15 Online:2020-05-05 Published:2020-05-05
  • Contact: Ming-Yang Zhou E-mail:zhoumy2010@gmail.com
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 61703281, 11547040, 61803266, 61503140, and 61873171), the PhD Start-Up Fund of Natural Science Foundation of Guangdong Province, China (Grant Nos. 2017A030310374 and 2016A030313036), the Science and Technology Innovation Commission of Shenzhen, China (Grant No. JCYJ20180305124628810), and the China Scholarship Council (Grant No. 201806340213).

摘要: The potential mechanisms of the spreading phenomena uncover the organizations and functions of various systems. However, due to the lack of valid data, most of early works are limited to the simulated process on model networks. In this paper, we track and analyze the propagation paths of real spreading events on two social networks: Twitter and Brightkite. The empirical analysis reveals that the spreading probability and the spreading velocity present the explosive growth within a short period, where the spreading probability measures the transferring likelihood between two neighboring nodes, and the spreading velocity is the growth rate of the information in the whole network. Besides, we observe the asynchronism between the spreading probability and the spreading velocity. To explain the interesting and abnormal issue, we introduce the time-varying spreading probability into the susceptible-infected (SI) and linear threshold (LT) models. Both the analytic and experimental results reproduce the spreading phenomenon in real networks, which deepens our understandings of spreading problems.

关键词: social network, information diffusion, spreading probability, asynchronism

Abstract: The potential mechanisms of the spreading phenomena uncover the organizations and functions of various systems. However, due to the lack of valid data, most of early works are limited to the simulated process on model networks. In this paper, we track and analyze the propagation paths of real spreading events on two social networks: Twitter and Brightkite. The empirical analysis reveals that the spreading probability and the spreading velocity present the explosive growth within a short period, where the spreading probability measures the transferring likelihood between two neighboring nodes, and the spreading velocity is the growth rate of the information in the whole network. Besides, we observe the asynchronism between the spreading probability and the spreading velocity. To explain the interesting and abnormal issue, we introduce the time-varying spreading probability into the susceptible-infected (SI) and linear threshold (LT) models. Both the analytic and experimental results reproduce the spreading phenomenon in real networks, which deepens our understandings of spreading problems.

Key words: social network, information diffusion, spreading probability, asynchronism

中图分类号:  (Complex systems)

  • 89.75.-k
87.23.Ge (Dynamics of social systems) 05.45.-a (Nonlinear dynamics and chaos)