IDEAS home Printed from https://ideas.repec.org/a/spr/comaot/v26y2020i4d10.1007_s10588-019-09298-1.html
   My bibliography  Save this article

Interoperable pipelines for social cyber-security: assessing Twitter information operations during NATO Trident Juncture 2018

Author

Listed:
  • Joshua Uyheng

    (Carnegie Mellon University)

  • Thomas Magelinski

    (Carnegie Mellon University)

  • Ramon Villa-Cox

    (Carnegie Mellon University)

  • Christine Sowa

    (Carnegie Mellon University)

  • Kathleen M. Carley

    (Carnegie Mellon University)

Abstract

Social cyber-security is an emergent field defining a multidisciplinary and multimethodological approach to studying and preserving the free and open exchange of information online. This work contributes to burgeoning scholarship in this field by advocating the use of interoperable pipelines of computational tools. We demonstrate the utility of such a pipeline in a case study of Twitter information operations during the NATO Trident Juncture Exercises in 2018. By integratively utilizing tools from machine learning, natural language processing, and dynamic network analysis, we uncover significant bot activity aiming to discredit NATO targeted to key allied nations. We further show how to extend such analysis through drill-down procedures on individual influencers and influential subnetworks. We reflect on the value of interoperable pipelines for accumulating and triangulating insights that enable social cyber-security analysts to draw relevant insights across various scales of granularity.

Suggested Citation

  • Joshua Uyheng & Thomas Magelinski & Ramon Villa-Cox & Christine Sowa & Kathleen M. Carley, 2020. "Interoperable pipelines for social cyber-security: assessing Twitter information operations during NATO Trident Juncture 2018," Computational and Mathematical Organization Theory, Springer, vol. 26(4), pages 465-483, December.
    • Handle: RePEc:spr:comaot:v:26:y:2020:i:4:d:10.1007_s10588-019-09298-1
    DOI: 10.1007/s10588-019-09298-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10588-019-09298-1
    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/s10588-019-09298-1?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. Matthew Benigni & Kenneth Joseph & Kathleen M. Carley, 2018. "Mining online communities to inform strategic messaging: practical methods to identify community-level insights," Computational and Mathematical Organization Theory, Springer, vol. 24(2), pages 224-242, June.
    2. Matthew Babcock & Ramon Alfonso Villa Cox & Sumeet Kumar, 2019. "Diffusion of pro- and anti-false information tweets: the Black Panther movie case," Computational and Mathematical Organization Theory, Springer, vol. 25(1), pages 72-84, March.
    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. Raúl M. Ortiz-Gaona & Marcos Postigo-Boix & José L. Melús-Moreno, 2021. "Extent prediction of the information and influence propagation in online social networks," Computational and Mathematical Organization Theory, Springer, vol. 27(2), pages 195-230, June.

    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:comaot:v:26:y:2020:i:4:d:10.1007_s10588-019-09298-1. 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: 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.