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Identification of Users in a Gambling Problem with the Use of Machine Learning

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Intelligent Information and Database Systems (ACIIDS 2024)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14796))

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Abstract

In this article, we address the pressing issue of problem gambling and the initiatives undertaken by bookmaking companies to foster responsible gambling. The primary objective of this research is to identify users at risk of developing gambling addiction. To achieve this, we employ machine learning techniques and preprocessing tools to acquire and anonymize user data. A comprehensive dataset is utilized to pinpoint individuals who are at a heightened risk.

The study specifically focuses on devising an automated method to detect early indicators of irresponsible gambling behaviours. By applying advanced machine learning algorithms to a tailored set of features, we aim to identify the initial signs of potential gambling issues. The methodology does not rely on a singular algorithm, ensuring a broad and effective approach to problem identification.

The efficacy of this approach is validated through computational experiments, which are conducted on real data and subsequently verified by specialists in the field of gambling addiction. The results demonstrate a significant capability in successfully identifying users who exhibit early signs of potential gambling problems. This research contributes to the academic understanding of problem gambling and offers practical solutions for responsible gambling initiatives.

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Author information

Authors and Affiliations

  1. Department of Machine Learning, University of Economics in Katowice, 1 Maja 50, 40-287, Katowice, Poland

    Tomasz Jach, Barbara Probierz, Jan Kozak, Piotr Stefański, Grzegorz Dziczkowski, Anita Hrabia, Przemysław Juszczuk, Szymon Głowania & Gabriel Wołek

  2. STS S.A. - Bookmaker Company, Porcelanowa 8, 40-246, Katowice, Poland

    Wojciech Sznapka, Łukasz Świerk & Natalia Joniec

Authors
  1. Tomasz Jach
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  2. Barbara Probierz
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  3. Jan Kozak
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  4. Piotr Stefański
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  5. Grzegorz Dziczkowski
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  6. Anita Hrabia
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  7. Przemysław Juszczuk
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  8. Szymon Głowania
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  9. Gabriel Wołek
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  10. Wojciech Sznapka
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  11. Łukasz Świerk
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  12. Natalia Joniec
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Corresponding author

Correspondence to Tomasz Jach .

Editor information

Editors and Affiliations

  1. Wroclaw University of Science and Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. University of Pau and Adour Countries, Pau, France

    Richard Chbeir

  3. Open University of Cyprus, Latsia, Cyprus

    Yannis Manolopoulos

  4. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  5. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  6. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Le Minh Nguyen

  7. Wrocław University of Science and Technology, Wrocław, Poland

    Krystian Wojtkiewicz

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Jach, T. et al. (2024). Identification of Users in a Gambling Problem with the Use of Machine Learning. In: Nguyen, N.T., et al. Intelligent Information and Database Systems. ACIIDS 2024. Lecture Notes in Computer Science(), vol 14796. Springer, Singapore. https://doi.org/10.1007/978-981-97-4985-0_21

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  • DOI: https://doi.org/10.1007/978-981-97-4985-0_21

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