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Applying Data Science to Behavioral Analysis of Online Gambling

  • Gambling (L Clark, Section Editor)
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Abstract

Purpose of Review

Gambling operators’ capacity to track gamblers in the online environment may enable identification of those users experiencing gambling harm. This review provides an update on research testing behavioral variables against indicators of disordered gambling. We consider the utility of machine learning algorithms in risk prediction, and challenges to be overcome.

Recent Findings

Disordered online gambling is associated with a range of behavioral variables, as well as other predictors including demographic and payment-related information. Machine learning is ideally suited to the task of combining these predictors in risk identification, although current research has yielded mixed success. Recent work enhancing the temporal resolution of behavioral analysis to characterize bet-by-bet changes may identify novel predictors of loss chasing.

Summary

Data science has considerable potential to identify high-risk online gambling, informed by principles of behavioral analysis. Identification may enable targeting of interventions to users who are most at risk.

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Funding

This work was supported by the Centre for Gambling Research at UBC core funding from the Province of British Columbia and the British Columbia Lottery Corporation (BCLC), as well as a research grant from BC Ministry of Finance to LC. XD is supported by a 4-year fellowship funding from UBC. LC receives funding from the Natural Sciences and Engineering Research Council (Canada).

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Authors and Affiliations

  1. Centre for Gambling Research at UBC, Department of Psychology, University of British Columbia, 2136 West Mall, Vancouver, British Columbia, V6T 1Z4, Canada

    Xiaolei Deng, Tilman Lesch & Luke Clark

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  1. Xiaolei Deng
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  2. Tilman Lesch
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  3. Luke Clark
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Corresponding author

Correspondence to Luke Clark.

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Conflict of Interest

Luke Clark is the Director of the Centre for Gambling Research at UBC, which is supported by funding from the Province of British Columbia and the British Columbia Lottery Corporation (BCLC), a Canadian Crown Corporation. The BCLC and BC Government has no constraints on publishing. LC has received speaking or reviewing honoraria from Svenska Spel (Sweden), National Association for Gambling Studies (Australia), National Center for Responsible Gaming (US), and Gambling Research Exchange Ontario (Canada). He has not received any further direct or indirect payments from the gambling industry or groups substantially funded by gambling. He has received royalties from Cambridge Cognition Ltd. relating to neurocognitive testing. XD and TL report no conflicts of interest.

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Deng, X., Lesch, T. & Clark, L. Applying Data Science to Behavioral Analysis of Online Gambling. Curr Addict Rep 6, 159–164 (2019). https://doi.org/10.1007/s40429-019-00269-9

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