IDEAS home Printed from https://ideas.repec.org/a/ids/injdan/v17y2025i1p1-19.html
   My bibliography  Save this article

Application of text mining analysis in understanding GameFi adoption

Author

Listed:
  • Yimiao Zhang
  • Jing Ren
  • Wenting Liu
  • Ding Ding

Abstract

Blockchain-based gaming industry has been expanding over the past two years, but the GameFi sector has yet to solve its biggest problem - the lack of mass gamer adoption. In this work, text mining was leveraged to study the adoption status of GameFi and explore the possible requirements and concerns of game players regarding blockchain games. Quora questions relating to GameFi were collected to examine the key topics discussed by GameFi users or potential users. Our findings disclosed that GameFi is in the early stage of the innovation diffusion process and has not been widely adopted by the public. Individuals are concerned about the risk and return of play-to-earn (P2E) games, and some potential users are deterred by the high entry barriers of GameFi. Through studying the opinions of players or potential players, this study sheds some light on the possible strategies for improving blockchain game design in the near future.

Suggested Citation

  • Yimiao Zhang & Jing Ren & Wenting Liu & Ding Ding, 2025. "Application of text mining analysis in understanding GameFi adoption," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 17(1), pages 1-19.
    • Handle: RePEc:ids:injdan:v:17:y:2025:i:1:p:1-19
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=144964
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    GameFi; P2E; play-to-earn; mass adoption; text analysis.;
    All these keywords.

    JEL classification:

    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:ids:injdan:v:17:y:2025:i:1:p:1-19. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=282 .

    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.