IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v456y2023ics0096300323002904.html
   My bibliography  Save this article

Contagion in social networks: On contagion thresholds

Author

Listed:
  • Keng, Ying Ying
  • Kwa, Kiam Heong

Abstract

Consider a story initiated by a set S of nodes belonging to a network. We assume that all the remaining nodes in the network have the same adoption threshold q such that each of them will accept the story if and only if the story has been accepted by at least a fraction q of its neighbors. Consequently, there is a maximum threshold q at and below which a full contagion (i.e. acceptance of the story by all nodes in the network) can occur from S, called the contagion threshold of S. We study how it is influenced by the neighborhood of S or by the global topology of the network. Firstly, we establish two algorithms to compute the contagion threshold of any given set of nodes in a network. Secondly, we show that the contagion threshold of a connected set in a tree is completely determined by the maximum degree of the nodes not in the set. Next, we derive bounds for the contagion threshold, while indicating when it preserves the neighborhood-inclusion pre-order and when the preservation may fail. Finally, we look at the structural characterization of the sets of nodes with high contagion thresholds.

Suggested Citation

  • Keng, Ying Ying & Kwa, Kiam Heong, 2023. "Contagion in social networks: On contagion thresholds," Applied Mathematics and Computation, Elsevier, vol. 456(C).
    • Handle: RePEc:eee:apmaco:v:456:y:2023:i:c:s0096300323002904
    DOI: 10.1016/j.amc.2023.128121
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300323002904
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2023.128121?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.

    References listed on IDEAS

    as
    1. Teruyoshi Kobayashi, 2015. "Trend-driven information cascades on random networks," Discussion Papers 1529, Graduate School of Economics, Kobe University.
    2. John Higgins & Tarun Sabarwal, 2021. "Control and Spread of Contagion in Networks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202201, University of Kansas, Department of Economics, revised Jan 2022.
    3. Douglas Guilbeault & Damon Centola, 2021. "Topological measures for identifying and predicting the spread of complex contagions," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    4. Damon Centola, 2019. "Influential networks," Nature Human Behaviour, Nature, vol. 3(7), pages 664-665, July.
    5. Xiaochen Wang & Yueheng Lan & Jinghua Xiao, 2019. "Anomalous structure and dynamics in news diffusion among heterogeneous individuals," Nature Human Behaviour, Nature, vol. 3(7), pages 709-718, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guilherme Ferraz de Arruda & Giovanni Petri & Pablo Martin Rodriguez & Yamir Moreno, 2023. "Multistability, intermittency, and hybrid transitions in social contagion models on hypergraphs," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Fabio Caccioli & Paolo Barucca & Teruyoshi Kobayashi, 2018. "Network models of financial systemic risk: a review," Journal of Computational Social Science, Springer, vol. 1(1), pages 81-114, January.
    3. Nie, Yanyi & Zhong, Xiaoni & Lin, Tao & Wang, Wei, 2022. "Homophily in competing behavior spreading among the heterogeneous population with higher-order interactions," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    4. Li, Yang & Sun, Hao & Xiong, Wanda & Xu, Genjiu, 2021. "Belief model of complex contagions on random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    5. James Flamino & Alessandro Galeazzi & Stuart Feldman & Michael W. Macy & Brendan Cross & Zhenkun Zhou & Matteo Serafino & Alexandre Bovet & Hernán A. Makse & Boleslaw K. Szymanski, 2023. "Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections," Nature Human Behaviour, Nature, vol. 7(6), pages 904-916, June.
    6. Roberto Araya, 2023. "Connecting Classrooms with Online Interclass Tournaments: A Strategy to Imitate, Recombine and Innovate Teaching Practices," Sustainability, MDPI, vol. 15(10), pages 1-25, May.
    7. 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).
    8. Anwesha Sengupta & Shashankaditya Upadhyay & Indranil Mukherjee & Prasanta K. Panigrahi, 2022. "Describing the effect of influential spreaders on the different sectors of Indian market: a complex networks perspective," Papers 2303.05432, arXiv.org.
    9. Teruyoshi Kobayashi & Tomokatsu Onaga, 2023. "Dynamics of diffusion on monoplex and multiplex networks: a message-passing approach," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 76(1), pages 251-287, July.

    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:apmaco:v:456:y:2023:i:c:s0096300323002904. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.