IDEAS home Printed from https://ideas.repec.org/a/spr/jeicoo/v19y2024i2d10.1007_s11403-023-00392-x.html
   My bibliography  Save this article

Knowledge diffusion in social networks under targeted attack and random failure: the resilience of communities

Author

Listed:
  • Piergiuseppe Morone

    (UnitelmaSapienza University of Rome)

  • Rocco Caferra

    (UnitelmaSapienza University of Rome)

  • Antonio Lopolito

    (University of Foggia)

Abstract

Knowledge diffusion is a complex and demanding process that requires coordination and collaboration between agents with different levels of knowledge, to establish fruitful learning interactions. In this paper, we develop an agent-based model to investigate how different behavioral/sociological rules can alter, strengthen, or weaken this process. We observe that, during normal times, different aggregation strategies are apparently irrelevant for determining differences in learning opportunities. However, under crisis, there is an observable outperformance of social structures with established communities, characterized by both strong ties (i.e., intense contacts within communities) and weak ties (i.e., knowledge spillover across communities). We further test system resilience, considering interruptions to the knowledge diffusion of expert agents and the random temporary removal of agents (simulating a viral outbreak). We discuss how these scenarios may explain economic phenomena and explore the implications for policies aimed at mitigating knowledge and economic inequalities.

Suggested Citation

  • Piergiuseppe Morone & Rocco Caferra & Antonio Lopolito, 2024. "Knowledge diffusion in social networks under targeted attack and random failure: the resilience of communities," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 19(2), pages 283-303, April.
    • Handle: RePEc:spr:jeicoo:v:19:y:2024:i:2:d:10.1007_s11403-023-00392-x
    DOI: 10.1007/s11403-023-00392-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11403-023-00392-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11403-023-00392-x?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.

    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:spr:jeicoo:v:19:y:2024:i:2:d:10.1007_s11403-023-00392-x. 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.springer.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.