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Analysis of casino online gambling data in relation to behavioural risk markers for high-risk gambling and player protection

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  • Simo Dragicevic
  • George Tsogas
  • Aleksandar Kudic

Abstract

The Internet gambling industry has witnessed tremendous growth in recent years. Nonetheless, our understanding of Internet problem gambling behaviour remains in its infancy. In this paper we build on previous research analysing behavioural markers for high-risk Internet gambling using a new casino data set of active real money Internet gamblers. We assess the first month of play following registration using four behavioural markers: trajectory, frequency, intensity and variability. Our findings identify groups of gamblers who show signs of potentially risky behaviours, specifically gambling intensity and frequency. These gamblers also spend time gambling on slots Internet games. These findings provide a basis for using behavioural analysis to educate players about risks associated with gambling. We suggest a framework for how this can be implemented. Further research leading to the identification of risk factors for problem gambling using new methodologies and data sets will increase the clinical understanding of Internet problem gamblers.

Suggested Citation

  • Simo Dragicevic & George Tsogas & Aleksandar Kudic, 2011. "Analysis of casino online gambling data in relation to behavioural risk markers for high-risk gambling and player protection," International Gambling Studies, Taylor & Francis Journals, vol. 11(3), pages 377-391, December.
    • Handle: RePEc:taf:intgms:v:11:y:2011:i:3:p:377-391
    DOI: 10.1080/14459795.2011.629204
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    Cited by:

    1. Jonathan Parke & Adrian Park & Andrew Harris & Jane Rigbye & Alex Blaszczynski, 2014. "Restricting Access: Self-Exclusion As A Gambling Harm Minimisation Measure In Great Britain," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 8(3), pages 52-94.
    2. Maris Catania & Mark D. Griffiths, 2021. "Understanding Online Voluntary Self-Exclusion in Gambling: An Empirical Study Using Account-Based Behavioral Tracking Data," IJERPH, MDPI, vol. 18(4), pages 1-11, February.

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