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Modeling the effects of social impact on epidemic spreading in complex networks

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  • Ni, Shunjiang
  • Weng, Wenguo
  • Zhang, Hui

Abstract

We investigate by mean-field analysis and extensive simulations the effects of social impact on epidemic spreading in various typical networks with two types of nodes: active nodes and passive nodes, of which the behavior patterns are modeled according to the social impact theory. In this study, nodes are not only the media to spread the virus, but also disseminate their opinions on the virus—whether there is a need for certain self-protection measures to be taken to reduce the risk of being infected. Our results indicate that the interaction between epidemic spreading and opinion dynamics can have significant influences on the spreading of infectious diseases and related applications, such as the implementation of prevention and control measures against the infectious diseases.

Suggested Citation

  • Ni, Shunjiang & Weng, Wenguo & Zhang, Hui, 2011. "Modeling the effects of social impact on epidemic spreading in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4528-4534.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:23:p:4528-4534
    DOI: 10.1016/j.physa.2011.07.042
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Wen, Xiangxi & Tu, Congliang & Wu, Minggong & Jiang, Xurui, 2018. "Fast ranking nodes importance in complex networks based on LS-SVM method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 11-23.
    2. Gao, Cai & Wei, Daijun & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2013. "A modified evidential methodology of identifying influential nodes in weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5490-5500.
    3. Wang, Xiaoyang & Wang, Ying & Zhu, Lin & Li, Chao, 2016. "A novel approach to characterize information radiation in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 94-105.
    4. Jin, Ziyang & Duan, Dongli & Wang, Ning, 2022. "Cascading failure of complex networks based on load redistribution and epidemic process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    5. Wei, Daijun & Deng, Xinyang & Zhang, Xiaoge & Deng, Yong & Mahadevan, Sankaran, 2013. "Identifying influential nodes in weighted networks based on evidence theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2564-2575.
    6. Pires, Marcelo A. & Crokidakis, Nuno, 2017. "Dynamics of epidemic spreading with vaccination: Impact of social pressure and engagement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 167-179.
    7. Youzhong Wang & Daniel Zeng & Bin Zhu & Xiaolong Zheng & Feiyue Wang, 2014. "Patterns of news dissemination through online news media: A case study in China," Information Systems Frontiers, Springer, vol. 16(4), pages 557-570, September.

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