Informação do projeto/bolsa

 
Nome do projeto/bolsa Online Gambling Addiction Detection
Descrição The exploration and practice of online gaming and betting in Portugal began on May 25, 2016, having been issued 11 licenses and registering about 1800 million euros of revenue at the end of 2017. According to the European Gaming and Betting Association, Europe currently represents the largest international market for online gambling, with a Gross Gaming Revenue (GGR) expected to reach €24.9 billion in 2020 [2]. To wit, online gambling is a major industry in every European country, generating billions of Euros in revenue for commercial actors and governments alike. Gambling should be regarded as a leisure and entertainment activity. When the player does not respect these values, gambling can generate detrimental effects that could result in an overall deterioration of social and familial relationships [3]. In 2012, the European Commission released a statement [5] highlighting the need for regulatory policies to aid in the detection of pathological gambling behaviors, citing “a responsibility to protect those citizens and families who suffer from a gambling addiction.” In Portugal, the Gambling Inspection and Regulation Service is “responsible for the control and regulation of gambling activities in casinos and bingo halls, as well as online gambling and betting.” To comply with operational objectives, this authority receives, on a daily basis, all data related to online gambling activities pursued by every user on every online platform with services that are accessible to Portuguese citizens. In spite of this prodigious collection of data, the authority still lacks appropriate tools for identifying gambling addicts. This authority acknowledges a profound scarcity of actionable data regarding the actual scope of gambling addiction, and a consequent lack of expertise about how best to deal with this problem. The same authority observes that “the human dimension and economical and social relevance of this issue (i.e., gambling addiction) demands scientific studies.” To answer this call, this project proposes an AI (Artificial Intelligence)-based tool that could capitalize on the vast amount of data collected every day and analyze online user behavior to model and detect the behaviors associated with addicted gamblers. The problem represents a major challenge for a few reasons: first, the massive amount of data involved (that will require efficient data-analysis algorithms); second, the temporal dimension of the phenomenon we intend to model; and third, the fact that we are trying to observe and affect behaviors associated with a very small fraction of the population. The analysis confronts an additional complication by virtue of the potentially infinite behaviors associated with various kinds of gamblers. To tackle this problem, we propose a system based on a version of Recurrent Neural Networks (RNNs) the architecture of which will be optimized by a neuroevolution algorithm. RNNs are ideal modes for addressing problems that can only be resolved by using previous events to predict the future events of a system; RNNs have been successfully applied in a plethora of different domains [6]. To effectively resolve the problem under consideration, this system must be able to render efficient comparisons of time series associated with different gamblers’ behaviors, in a way that also takes the temporal dimension of the problem into account. The system, therefore, must be able to: (1) identify common behavioral patterns among gamblers within in an acceptable timeframe; (2) detect actions that are representative of a risky behavior in the context of gambling; and (3) run in real-time, to allow for continuous control of gambling activities. Successful implementation of the system and its integration with the system currently in use by the gambling control authority will enable efficient modeling and detection of online user behaviors associated with gambling addiction. Armed with this information, the authority could deploy all actions it regards as necessary. The social impact of the project is enormous, given its inherent capacity to reduce the social costs associated with gambling addiction. In sum, the project will address a socio-economic problem that at least one public authority regards as critical in the following ways: analyzing a large volume of administrative micro-data derived from the routine operation of the gambling control authority; implementing a new system that can model and detect online user behaviors associated with pathological gambling, by proposing a state-of-the-art AI system; and furnishing the gambling authority with a tool for the successful achievement of its regulatory duties.
Financiador FCT - Fundação para a Ciência e a Tecnologia, I.P.
Programa de financiamento 3599-PPCDT
ID do projeto/bolsa 154432
Referência DSAIPA/DS/0022/2018
FundRef URI http://www.fct.pt/apoios/projectos/consulta/vglobal_projecto.phtml.en?idProjecto=154432&idElemConcurso=12346
Data de início 2019-01-10
Data de fim 2022-01-09
Valor financiado 295,291.00 €
 

Informação do relatório

 

Sumário

Data do relatório 2026-05-02
Número de documentos 2

Documentos por repositório

estudogl 2

Documentos por tipo de documento

master thesis 2

Documentos por tipo de accesso

openAccess 2

Documentos

Evolution of Data Augmentation Strategies Applied to Medical Imaging Pereira, Sofia da Silva Acesso aberto Dissertação de mestrado 2021 estudogl https://hdl.handle.net/10316/98188
Probabilistic Grammatical Evolution Cunha, Jessica Megane Taveira da Acesso aberto Dissertação de mestrado 2021 estudogl https://hdl.handle.net/10316/96066