Kimura, Shunya; (2025) Typologies of Online Gambling Behaviours in Great Britain: Insights from Geographic Smart Data Analysis. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Online gambling is a rapidly expanding pastime, offering convenience and entertainment through access to a wide range of services. Yet, growing evidence of its potential harms manifests concerns about the ways in which individuals engage with online platforms. This thesis argues that traditional survey-led investigations present incomplete representations of gambling behaviours, compounded by vagaries of self-reported data and inference about infrequent occurrences from small sampling fractions of the population at large. Accordingly, this thesis employs a data-intensive analysis of c. 1.2 million online accounts held by active and dormant users to characterise online gambling behaviours across Great Britain (GB) throughout 2022. Central to the research is a comprehensive dataset obtained from one of the 'Big Five' British gambling operators, encompassing complete transactional and registration data for verified customers over a 12-month period. By restructuring the raw data and deriving detailed features of play, the thesis develops a highly differentiated view of gambling behaviours. These operator-specific insights are then reconciled with findings from nationally representative surveys, demonstrating how geographically granular, behaviour-based evidence can capture new depth of gambling engagement not available in social surveys. A combination of dimensionality reduction and clustering methods suggests a typology of 12 distinctive behaviours. Each type is rigorously profiled and contextualised using open data sources to uncover demographic and socio-economic factors that may shape engagement patterns. Finally, the study extends these insights to small-area geographies across GB by modelling probabilities that neighbourhood populations align with each of the identified gambler types. Through this integrated examination, the thesis underscores the indispensable value of Smart Data in yielding a more comprehensive and balanced understanding of online gambling’s societal impact. By illuminating the multifaceted nature of gambling behaviours and potential harms, the findings establish a robust evidence base to guide policymaking, target interventions and advance research in this fast-evolving arena.

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