IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v387y2008i2p623-630.html
   My bibliography  Save this article

How community structure influences epidemic spread in social networks

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437107010254
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2007.09.039?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Hernández, G. & Martín del Rey, A., 2022. "Community-distributed compartmental models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    4. 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.
    5. Chen, Peng & Qi, Mingze & Yan, Liang & Duan, Xiaojun, 2024. "Diffusion capacity analysis of complex network based on the cluster distribution," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    6. 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.
    7. 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.
    8. 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.
    9. Ma, Jinlong & Wang, Peng, 2024. "Impact of community networks with higher-order interaction on epidemic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    10. 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.
    11. 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.
    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. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:387:y:2008:i:2:p:623-630. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.