IDEAS home Printed from https://ideas.repec.org/a/nat/nathum/v3y2019i7d10.1038_s41562-019-0605-7.html
   My bibliography  Save this article

Anomalous structure and dynamics in news diffusion among heterogeneous individuals

Author

Listed:
  • Xiaochen Wang

    (Beijing University of Posts and Telecommunications)

  • Yueheng Lan

    (Beijing University of Posts and Telecommunications
    Beijing University of Posts and Telecommunications)

  • Jinghua Xiao

    (Beijing University of Posts and Telecommunications
    Beijing University of Posts and Telecommunications)

Abstract

Previous research has suggested that well-connected nodes in a network (commonly referred to as hubs) are better at spreading information than those with fewer connections (ordinary users). Here we investigate the roles of nodes with different numbers of connections by studying how people share news online. Quantitative analysis shows that users without many connections can sometimes spread news more effectively than well-connected users when the diffusion pattern has dendrite-like paths that reach far into the network, leading to a non-Gaussian distance distribution. When the hubs dominate, however, the distribution is Gaussian. Enhanced interactions among ordinary users are the key to the emergence of non-Gaussian characteristics. Finally, we introduce a message-passing model that reproduces the observed diffusion features. This model shows that patterns dominated by either hubs or ordinary users can be clearly demarcated by measuring the average number of forwards.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:nathum:v:3:y:2019:i:7:d:10.1038_s41562-019-0605-7
    DOI: 10.1038/s41562-019-0605-7
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41562-019-0605-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/s41562-019-0605-7?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. 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).
    2. Keng, Ying Ying & Kwa, Kiam Heong, 2023. "Contagion in social networks: On contagion thresholds," Applied Mathematics and Computation, Elsevier, vol. 456(C).
    3. Ma, Ning & Yu, Guang & Jin, Xin, 2024. "Dynamics of competing public sentiment contagion in social networks incorporating higher-order interactions during the dissemination of public opinion," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).

    More about this item

    Statistics

    Access and download statistics

    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:nat:nathum:v:3:y:2019:i:7:d:10.1038_s41562-019-0605-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    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.