IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v587y2022ics0378437121007834.html
   My bibliography  Save this article

Message passing approach for social contagions based on the trust probability with multiple influence factors

Author

Listed:
  • Leng, Hui
  • Zhao, Yi
  • Wang, Dong

Abstract

In social contagions, an individual to trust the behavioral information transmitted by neighbors depends on the level of the social status of neighbors as well as the closeness degree with neighbors. From the view of network topology, we propose the trust probability with multiple influence factors: node degree and the number of common neighbors. Furthermore, a weight factor is set to adjust the influence extent of the above two factors. As a result, in the context of the trust probability, we investigate social contagions with focus on social reinforcement and memory effect on networks, which are modeled by the threshold model. The message passing approach is adopted so as to formulate the state evolution of each node on the basis of network topology. Through extensive numerical simulations, we find that the trust probability can suppress social contagions, so does increasing the trust probability gap. Notably, the number of common neighbors as an influence factor of the trust probability is able to increase the final behavior adoption size, while node degree takes the opposite effect. The theoretical results are confirmed to agree well with the numerical results by the Monte Carlo method.

Suggested Citation

  • Leng, Hui & Zhao, Yi & Wang, Dong, 2022. "Message passing approach for social contagions based on the trust probability with multiple influence factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
  • Handle: RePEc:eee:phsmap:v:587:y:2022:i:c:s0378437121007834
    DOI: 10.1016/j.physa.2021.126510
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437121007834
    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.2021.126510?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. Wang, Wei & Chen, Xiao-Long & Zhong, Lin-Feng, 2018. "Social contagions with heterogeneous credibility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 604-610.
    2. Hao Peng & Wangxin Peng & Dandan Zhao & Zhaolong Hu & Jianmin Han & Zhonglong Zheng, 2020. "Impact of Immunization Strategies on the Dynamics of Social Contagions," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-9, August.
    3. Peng, Hao & Peng, Wangxin & Zhao, Dandan & Wang, Wei, 2020. "Impact of the heterogeneity of adoption thresholds on behavior spreading in complex networks," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. 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).

    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. 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).
    2. Wang, Yuyao & Bu, Zhan & Yang, Huan & Li, Hui-Jia & Cao, Jie, 2021. "An effective and scalable overlapping community detection approach: Integrating social identity model and game theory," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    3. Tian, Yang & Zhu, Xuzhen & Yang, Qiwen & Tian, Hui & Cui, Qimei, 2022. "Propagation characteristic of adoption thresholds heterogeneity in double-layer networks with edge weight distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    4. Yang, Qiwen & Zhu, Xuzhen & Tian, Yang & Wang, Guanglu & Zhang, Yuexia & Chen, Lei, 2021. "The influence of heterogeneity of adoption thresholds on limited information spreading," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    5. Huo, Liang’an & Yu, Yue, 2023. "The impact of the self-recognition ability and physical quality on coupled negative information-behavior-epidemic dynamics in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    6. Zhang, Gui-Qing & Baró, Jordi & Cheng, Fang-Yin & Huang, He & Wang, Lin, 2019. "Avalanche dynamics of a generalized earthquake model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1463-1471.
    7. Yuda Wang & Gang Li, 2018. "The Spreading of Information in Online Social Networks through Cellular Automata," Complexity, Hindawi, vol. 2018, pages 1-9, November.
    8. Wang, Jianwei & Wang, Siyuan & Wang, Ziwei, 2022. "Robustness of spontaneous cascading dynamics driven by reachable area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    9. Wei Duan, 2021. "Matrix-Based Formulation of Heterogeneous Individual-Based Models of Infectious Diseases: Using SARS Epidemic as a Case Study," IJERPH, MDPI, vol. 18(11), pages 1-20, May.
    10. Shang, Jiaxing & Wu, Hongchun & Zhou, Shangbo & Zhong, Jiang & Feng, Yong & Qiang, Baohua, 2018. "IMPC: Influence maximization based on multi-neighbor potential in community networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1085-1103.
    11. Qian, Qian & Yang, Yang & Gu, Jing & Feng, Hairong, 2019. "Information authenticity, spreading willingness and credit risk contagion – A dual-layer network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).

    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:587:y:2022:i:c:s0378437121007834. 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: 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.