IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0240693.html
   My bibliography  Save this article

Inside the decentralised casino: A longitudinal study of actual cryptocurrency gambling transactions

Author

Listed:
  • Oliver J Scholten
  • David Zendle
  • James A Walker

Abstract

Decentralised gambling applications are a new way for people to gamble online. Decentralised gambling applications are distinguished from traditional online casinos in that players use cryptocurrency as a stake. Also, rather than being stored on a single centralised server, decentralised gambling applications are stored on a cryptocurrency’s blockchain. Previous work in the player behaviour tracking literature has examined the spending profiles of gamblers on traditional online casinos. However, similar work has not taken place in the decentralised gambling domain. The profile of gamblers on decentralised gambling applications are therefore unknown. This paper explores 2,232,741 transactions from 24,234 unique addresses to three such applications operating atop the Ethereum cryptocurrency network over 583 days. We present spending profiles across these applications, providing the first detailed summary of spending behaviours in this technologically advanced domain. We find that the typical player spends approximately $110 equivalent across a median of 6 bets in a single day, although heavily involved bettors spend approximately $100,000 equivalent over a median of 644 bets across 35 days. Our findings suggest that the average decentralised gambling application player spends less than in other online casinos overall, but that the most heavily involved players in this new domain spend substantially more. This study also demonstrates the use of these applications as a research platform, specifically for large scale longitudinal in-vivo data analysis.

Suggested Citation

  • Oliver J Scholten & David Zendle & James A Walker, 2020. "Inside the decentralised casino: A longitudinal study of actual cryptocurrency gambling transactions," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-18, October.
    • Handle: RePEc:plo:pone00:0240693
    DOI: 10.1371/journal.pone.0240693
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0240693
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0240693&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0240693?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
    ---><---

    References listed on IDEAS

    as
    1. Kahlil S. Philander, 2014. "Identifying high-risk online gamblers: a comparison of data mining procedures," International Gambling Studies, Taylor & Francis Journals, vol. 14(1), pages 53-63, August.
    2. Nicola Adami & Sergio Benini & Alberto Boschetti & Luca Canini & Florinda Maione & Matteo Temporin, 2013. "Markers of unsustainable gambling for early detection of at-risk online gamblers," International Gambling Studies, Taylor & Francis Journals, vol. 13(2), pages 188-204, August.
    3. Tuomo Kainulainen, 2019. "A new measure of risk-taking in gambling," International Gambling Studies, Taylor & Francis Journals, vol. 19(1), pages 167-182, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhengjie Huang & Zhenguang Liu & Jianhai Chen & Qinming He & Shuang Wu & Lei Zhu & Meng Wang, 2022. "Who is Gambling? Finding Cryptocurrency Gamblers Using Multi-modal Retrieval Methods," Papers 2211.14779, arXiv.org.

    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.

      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:plo:pone00:0240693. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

      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.