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Early Detection of Problem Gambling based on Behavioral Changes using Shapelets

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Tomohiro TakagiAuthors Info & Claims

WI '19: IEEE/WIC/ACM International Conference on Web Intelligence

Pages 367 - 372

https://doi.org/10.1145/3350546.3352549

Published: 14 October 2019 Publication History

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Abstract

Recent years have seen strides achieved in the field of behavior analysis by using online gambling data. However, studies on time-series behavioral changes remain inadequate. In this study, we propose a classifier that quantifies changes in the player’s time series of online gambling behavioral data by using distance measurement with shapelet for the early detection of behaviors in players that could lead to problem gambling. We investigated the prediction capabilities of shapelets that represent behavioral change patterns, and the results showed that shapelet features can improve predictive accuracy. Furthermore, based on this result, we found characteristic behavioral changes leading to problem gambling, such as loss chasing. Subsequently, we demonstrated a possibility for improvements in accuracy using these behavioral change patterns based on expert knowledge.

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Ghaharian KAbarbanel BPhung DPuranik PKraus SFeldman ABernhard B(2022)Applications of data science for responsible gambling: a scoping reviewInternational Gambling Studies10.1080/14459795.2022.213575323:2(289-312)Online publication date: 8-Nov-2022
https://doi.org/10.1080/14459795.2022.2135753
Chakrabarty STalwadker RMukherjee TDemartini GZuccon GCulpepper JHuang ZTong H(2021)ScarceGANProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482474(140-150)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482474

Index Terms

Early Detection of Problem Gambling based on Behavioral Changes using Shapelets
1. Information systems
2. Theory of computation

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WI '19: IEEE/WIC/ACM International Conference on Web Intelligence

October 2019

507 pages

ISBN:9781450369343

DOI:10.1145/3350546

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 October 2019

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WI '19

WI '19: IEEE/WIC/ACM International Conference on Web Intelligence

October 14 - 17, 2019

Thessaloniki, Greece

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Ghaharian KAbarbanel BPhung DPuranik PKraus SFeldman ABernhard B(2022)Applications of data science for responsible gambling: a scoping reviewInternational Gambling Studies10.1080/14459795.2022.213575323:2(289-312)Online publication date: 8-Nov-2022
https://doi.org/10.1080/14459795.2022.2135753
Chakrabarty STalwadker RMukherjee TDemartini GZuccon GCulpepper JHuang ZTong H(2021)ScarceGANProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482474(140-150)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482474

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Abstract

References

Cited By

Index Terms

Recommendations

Migration from social casino games to gambling

Impact of Internet gambling on problem gambling among adolescents in Italy

Gambling prevalence and gambling problems amongst land-based-only, online-only and mixed-mode gamblers in Australia: A national study

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