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How community structure influences epidemic spread in social networks

Author

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  • Wu, Xiaoyan
  • Liu, Zonghua

Abstract

Two key features of social networks are the community structure and the high clustering coefficient. For understanding their influences on dynamical processes, we present a model with both an adjustable clustering coefficient and an adjustable degree of community. This model has an invariant degree distribution when its clustering coefficient is being adjusted. We find that the efficiency of epidemic spreading in this model depends mainly on the degree of community and decreases with increase of the degree of community. For a fixed degree of community, the efficiency will decrease with increase of the clustering coefficient. Numerical simulations have confirmed the theoretic analysis.

Suggested Citation

  • Wu, Xiaoyan & Liu, Zonghua, 2008. "How community structure influences epidemic spread in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 623-630.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:2:p:623-630
    DOI: 10.1016/j.physa.2007.09.039
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    Citations

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    Cited by:

    1. Zhang, Ruixia & Li, Deyu, 2017. "Rumor propagation on networks with community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 375-385.
    2. Kotnis, Bhushan & Kuri, Joy, 2016. "Cost effective campaigning in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 670-681.
    3. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2015. "Epidemic spreading on complex networks with overlapping and non-overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 171-182.
    4. Prasha Shrestha & Arun Sathanur & Suraj Maharjan & Emily Saldanha & Dustin Arendt & Svitlana Volkova, 2020. "Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-28, March.
    5. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2016. "Targeted revision: A learning-based approach for incremental community detection in dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 70-85.
    6. Tung Manh Ho & Hong Kong T. Nguyen & Thu-Trang Vuong & Quan-Hoang Vuong, 2017. "On the Sustainability of Co-Authoring Behaviors in Vietnamese Social Sciences: A Preliminary Analysis of Network Data," Sustainability, MDPI, vol. 9(11), pages 1-21, November.
    7. Tung Manh Ho & Hong Kong Nguyen-To & Thu-Trang Vuong & Quan-Hoang Vuong, 2017. "Social Network Sustainability Metrics: A Study of Co-authoring Behaviors in the Social Sciences, Using 2008-2017 Scopus Data for Vietnam," Working Papers CEB 17-027, ULB -- Universite Libre de Bruxelles.
    8. Hernández, G. & Martín del Rey, A., 2022. "Community-distributed compartmental models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    9. Medvedev, Alexey & Kertesz, Janos, 2017. "Empirical study of the role of the topology in spreading on communication networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 12-19.
    10. Han, Dun & Sun, Mei & Li, Dandan, 2015. "Epidemic process on activity-driven modular networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 354-362.
    11. Guan, Yuan-Pan & You, Zhi-Qiang & Han, Xiao-Pu, 2016. "Reconstruction of social group networks from friendship networks using a tag-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 485-492.
    12. Jia, Peng & Liu, Jiayong & Fang, Yong & Liu, Liang & Liu, Luping, 2018. "Modeling and analyzing malware propagation in social networks with heterogeneous infection rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 240-254.
    13. González-Parra, Gilberto & Acedo, L. & Villanueva Micó, Rafael-J. & Arenas, Abraham J., 2010. "Modeling the social obesity epidemic with stochastic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3692-3701.
    14. Colman, E.R. & Rodgers, G.J., 2013. "Complex scale-free networks with tunable power-law exponent and clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5501-5510.
    15. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Qiu, Tian & Shi, Yong-Dong & Zhong, Chen-Yang, 2015. "Coupled effects of local movement and global interaction on contagion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 482-491.
    16. Gong Kai & Kang Li, 2018. "A New K-Shell Decomposition Method for Identifying Influential Spreaders of Epidemics on Community Networks," Journal of Systems Science and Information, De Gruyter, vol. 6(4), pages 366-375, August.

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