Machine learning to help predict online gambling addiction

A new system designed to help users control their online gambling, provides an ‘early warning’ notification to gamblers who show signs of addiction. The software, developed by teams at City University London and gaming analytics start-up BetBuddy, traces users’ gambling habits and points to potential signs of risk by comparing data collected from previous addicts who have since asked to be blocked from online game sites. The underpinning computer models have been developed according to the latest findings from psychological pathway studies into gambling addictions. The research was funded by Innovate UK, under its Data Exploration programme. The system is also backed by the RCUK Digital Economy Theme, the Engineering and Physical Sciences Research Council (EPSRC), the Economic and Social Research Council (ESRC) and the Defence Science and Technology Laboratory…


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