IDEAS home Printed from https://ideas.repec.org/a/bla/sysdyn/v40y2024i3ne1772.html
   My bibliography  Save this article

Integrating AI language models in qualitative research: Replicating interview data analysis with ChatGPT

Author

Listed:
  • Mohammad S. Jalali
  • Ali Akhavan

Abstract

The recent advent of artificial intelligence (AI) language tools like ChatGPT has opened up new opportunities in qualitative research. We revisited a previous project on obesity prevention interventions, where we developed a causal loop diagram through in‐depth interview data analysis. Utilizing ChatGPT in our replication process, we compared its results against our original approach. We discuss that ChatGPT contributes to improved efficiency and unbiased data processing; however, it also reveals limitations in context understanding. Our findings suggest that AI language tools currently have great potential to serve as an augmentative tool rather than a replacement for the intricate analytical tasks performed by humans. With ongoing advancements, AI technologies may soon offer more substantial support in enhancing qualitative research capabilities, an area that deserves more investigation. © 2024 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

Suggested Citation

  • Mohammad S. Jalali & Ali Akhavan, 2024. "Integrating AI language models in qualitative research: Replicating interview data analysis with ChatGPT," System Dynamics Review, System Dynamics Society, vol. 40(3), July.
  • Handle: RePEc:bla:sysdyn:v:40:y:2024:i:3:n:e1772
    DOI: 10.1002/sdr.1772
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/sdr.1772
    Download Restriction: no

    File URL: https://libkey.io/10.1002/sdr.1772?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:bla:sysdyn:v:40:y:2024:i:3:n:e1772. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1111/0883-7066 .

    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.