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Cooperative and Competitive Dynamics Model for Information Propagation in Online Social Networks

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  • Yaming Zhang
  • Chaosheng Tang
  • Li Weigang

Abstract

Traditional empirical models of propagation consider individual contagion as an independent process, thus spreading in isolation manner. In this paper, we study how different contagions interact with each other as they spread through the network in order to propose an alternative dynamics model for information propagation. The proposed model is a novel combination of Lotka-Volterra cooperative model and competitive model. It is assumed that the interaction of one message on another is flexible instead of always negative. We prove that the impact of competition depends on the critical speed of the messages. By analyzing the differential equations, one or two stable equilibrium points can be found under certain conditions. Simulation results not only show the correctness of our theoretical analyses but also provide a more attractive conclusion. Different types of messages could coexist in the condition of high critical speed and intense competitive environment, or vice versa. The messages will benefit from the high critical speed when they are both competitive, and adopting a Tit-for-Tat strategy is necessary during the process of information propagation.

Suggested Citation

  • Yaming Zhang & Chaosheng Tang & Li Weigang, 2014. "Cooperative and Competitive Dynamics Model for Information Propagation in Online Social Networks," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-12, July.
  • Handle: RePEc:hin:jnljam:610382
    DOI: 10.1155/2014/610382
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    Cited by:

    1. Wang, Tao & He, Juanjuan & Wang, Xiaoxia, 2018. "An information spreading model based on online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 488-496.
    2. Zhang, Jing & Wang, Xiaoli & Xie, Yanxi & Wang, Meihua, 2022. "Research on multi-topic network public opinion propagation model with time delay in emergencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).

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