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Layered SIRS model of information spread in complex networks

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  • Zhang, Yuexia
  • Pan, Dawei

Abstract

In complex network research, the infectious disease model is often used to study transmission mechanisms and interference factors of information; consequently, they are essential for the prediction and control of information transmission. The conventional SIRS epidemic model has a wide range of applications and is theoretically mature. However, it does not stratify the nodes in a network, and fails to reflect the characteristics of different nodes. To solve this problem, we propose a layered SIRS information transmission model (L-SIRS) . Depending on the node influence, we assign the nodes in the network to high- and low-influence layers and establish an intra- and inter-layer information transmission mechanism. The transmission threshold and equilibrium point of this model are analyzed theoretically. To reduce the transmission of online public opinions, two kinds of information transmission interference strategies, namely, information blocking and information dredging, are designed to study their influence on information transmission. Finally, combine with practice, the simulation results indicate that the L-SIRS model can more accurately describe network information transmission and both information blocking and information dredging can effectively inhibit the spread of information.

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  • Zhang, Yuexia & Pan, Dawei, 2021. "Layered SIRS model of information spread in complex networks," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    • Handle: RePEc:eee:apmaco:v:411:y:2021:i:c:s0096300321006135
    DOI: 10.1016/j.amc.2021.126524
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    References listed on IDEAS

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    1. Liu, Lijun & Wei, Xiaodan & Zhang, Naimin, 2019. "Global stability of a network-based SIRS epidemic model with nonmonotone incidence rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 587-599.
    2. Wang, Zhishuang & Guo, Quantong & Sun, Shiwen & Xia, Chengyi, 2019. "The impact of awareness diffusion on SIR-like epidemics in multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 349(C), pages 134-147.
    3. Wang, Yi & Cao, Jinde & Alofi, Abdulaziz & AL-Mazrooei, Abdullah & Elaiw, Ahmed, 2015. "Revisiting node-based SIR models in complex networks with degree correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 75-88.
    4. Liu, Li & Luo, Xiaofeng & Chang, Lili, 2017. "Vaccination strategies of an SIR pair approximation model with demographics on complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 282-290.
    5. Lahrouz, Aadil & Omari, Lahcen, 2013. "Extinction and stationary distribution of a stochastic SIRS epidemic model with non-linear incidence," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 960-968.
    6. Cao, Zhongwei & Feng, Wei & Wen, Xiangdan & Zu, Li & Gao, Jinyao, 2020. "Nontrivial periodic solution of a stochastic seasonal rabies epidemic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    7. Saif, M. Ali, 2019. "Epidemic threshold for the SIRS model on the networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    8. Zhao, Laijun & Cui, Hongxin & Qiu, Xiaoyan & Wang, Xiaoli & Wang, Jiajia, 2013. "SIR rumor spreading model in the new media age," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 995-1003.
    9. Yuan, Xinpeng & Wang, Fang & Xue, Yakui & Liu, Maoxing, 2018. "Global stability of an SIR model with differential infectivity on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 443-456.
    10. Liu, Qun & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed & Ahmad, Bashir, 2020. "A stochastic SIRS epidemic model with logistic growth and general nonlinear incidence rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    11. Huo, Jingjing & Zhao, Hongyong, 2016. "Dynamical analysis of a fractional SIR model with birth and death on heterogeneous complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 41-56.
    12. Zelong Yi & Xiaokun Wu & Fan Li, 2018. "Ranking Spreaders in Complex Networks Based on the Most Influential Neighbors," Discrete Dynamics in Nature and Society, Hindawi, vol. 2018, pages 1-6, August.
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    Cited by:

    1. Chakir, Yassine, 2023. "Global approximate solution of SIR epidemic model with constant vaccination strategy," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    2. Zhu, Hongmiao & Jin, Zhen, 2023. "A dynamics model of knowledge dissemination in a WeChat Group from perspective of duplex networks," Applied Mathematics and Computation, Elsevier, vol. 454(C).

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