IDEAS home Printed from https://ideas.repec.org/a/now/fntisy/2900000037.html
   My bibliography  Save this article

Misinformation Detection: A Survey of AI Techniques and Research Opportunities

Author

Listed:
  • Gabrielle Taylor
  • Wenting Jiang
  • Xiao Qin
  • Ashish Gupta

Abstract

This survey highlights the evolution of techniques within misinformation detection. Misinformation has become increasingly prevalent on the Internet by the day and progressively more threatening. Individuals who are inaccurately informed tend to make misinformed decisions which have led to voting scandals, traffic accidents, and even health concerns. We are motivated to address a research gap by analyzing misinformation detection’s overall progress and exposing the weaknesses that provide research opportunities. Our findings will further advance the work of misinformation detection and bring light to unique ways to tackle the issue. Notably, we discuss the significance of misinformation detection systems and present the problems resulting from misinformation, the techniques for detection, and open issues within this research. Misinformation is becoming an issue that requires more attention and improved systems. We believe that our systematic review and synthesis of state-of-art research will cultivate a path for these developments.

Suggested Citation

  • Gabrielle Taylor & Wenting Jiang & Xiao Qin & Ashish Gupta, 2024. "Misinformation Detection: A Survey of AI Techniques and Research Opportunities," Foundations and Trends(R) in Information Systems, now publishers, vol. 8(2), pages 66-147, October.
  • Handle: RePEc:now:fntisy:2900000037
    DOI: 10.1561/2900000037
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1561/2900000037
    Download Restriction: no

    File URL: https://libkey.io/10.1561/2900000037?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
    ---><---

    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:now:fntisy:2900000037. 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: Lucy Wiseman (email available below). General contact details of provider: http://www.nowpublishers.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.