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Authors: Kurt Dylan Buttigieg ; Mark Anthony Caruana and David Suda

Affiliation: University of Malta, Malta

Keyword(s): Artificial Neural Networks, Bayesian Neural Networks, Problematic Gambling.

Abstract: Responsible gaming has gained traction in recent years due to the harmful nature of compulsive online gambling and the increased awareness on the unfavourable consequences arising from this type of gambling. In Malta, legislation passed in 2018 places the onus of responsibility on online gaming companies has made studying this problem even more important. The focus of this research paper is to apply multistage and two-stage artificial neural networks (ANN), and two-stage Bayesian neural networks (BNN), to the responsible gaming problem by training models that can predict the gambling-risk of a player as a multiclass classification problem. The models are trained using data from gambling session histories provided by a gaming company based in Malta. These models will then be compared using different performance metrics. It is shown that, while all approaches considered have their strengths, multiclass artificial neural networks perform best in terms of overall accuracy while the two-s tage Bayesian neural network model performs best in classifying the most important class, the one where the players have a high risk of becoming problematic gamblers, and also second best at classifying the medium risk class. (More)

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Paper citation in several formats:
Buttigieg, K.; Caruana, M. and Suda, D. (2022). Identifying Problematic Gamblers using Multiclass and Two-stage Binary Neural Network Approaches. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-547-0; ISSN 2184-433X, SciTePress, pages 336-342. DOI: 10.5220/0010821100003116

@conference{icaart22,
author={Kurt Dylan Buttigieg. and Mark Anthony Caruana. and David Suda.},
title={Identifying Problematic Gamblers using Multiclass and Two-stage Binary Neural Network Approaches},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2022},
pages={336-342},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010821100003116},
isbn={978-989-758-547-0},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Identifying Problematic Gamblers using Multiclass and Two-stage Binary Neural Network Approaches
SN - 978-989-758-547-0
IS - 2184-433X
AU - Buttigieg, K.
AU - Caruana, M.
AU - Suda, D.
PY - 2022
SP - 336
EP - 342
DO - 10.5220/0010821100003116
PB - SciTePress

- Science and Technology Publications, Lda.
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