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Impact of Immunization Strategies on the Dynamics of Social Contagions

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  • Hao Peng
  • Wangxin Peng
  • Dandan Zhao
  • Zhaolong Hu
  • Jianmin Han
  • Zhonglong Zheng

Abstract

Immunization strategies on complex networks are effective methods to control the spreading dynamics on complex networks, which change the topology and connectivity of the underlying network, thereby affecting the dynamics process of propagation. Here, we use a non-Markovian threshold model to study the impact of immunization strategies on social contagions, in which the immune index greater than (or equal to) 0 corresponds to targeted (random) immunization, and when the immune index is less than 0, the probability of an individual being immunized is inversely related to the degree of the individual. A generalized edge-based compartmental theory is developed to analyze the dynamics of social contagions under immunization, and theoretical predictions are very consistent with simulation results. We find that increasing the immune index or increasing the immune ratio will reduce the final adoption size and increase the outbreak threshold, in other words, make the residual network after immunization not conducive to social contagions. Interestingly, enhancing the network heterogeneity is proved to help improve the immune efficiency of targeted immunization. Besides, the dependence of the outbreak threshold on the network heterogeneity is correlated with the immune ratio and immune index.

Suggested Citation

  • Hao Peng & Wangxin Peng & Dandan Zhao & Zhaolong Hu & Jianmin Han & Zhonglong Zheng, 2020. "Impact of Immunization Strategies on the Dynamics of Social Contagions," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-9, August.
  • Handle: RePEc:hin:jnddns:5284348
    DOI: 10.1155/2020/5284348
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    Cited by:

    1. Leng, Hui & Zhao, Yi & Wang, Dong, 2022. "Message passing approach for social contagions based on the trust probability with multiple influence factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    2. Cui, Yajuan & Wei, Ruichen & Tian, Yang & Tian, Hui & Zhu, Xuzhen, 2022. "Information propagation influenced by individual fashion-passion trend on multi-layer weighted network," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).

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