Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and Segmentation

Detalhes bibliográficos
Autor(a) principal: Lannes, Leonardo Motta Perazzo
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/135874
Resumo: Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
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spelling Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and SegmentationArtificial IntelligenceBig DataClusteringData ScienceMachine LearningSegmentationUnsupervised LearningProject Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceOnline gambling has become an increasingly relevant activity in the last years and is now available through a wide variety of technologies and platforms. This can be seen as an important addition to the entertainment industry since it has the potential of generating great economic impacts. The phenomenon, however, is not free of concerns considering that, like in any other type of gambling activities, online gamblers are susceptible to developing behavioral addiction. This has become a reason of concern to many governmental bodies around the world which are studying this issue due to its social impacts on the population. In this context machine learning algorithms can be applied to understand the behavior of online gamblers and to identify the characteristics of gambling addiction. This work project has the objective of segmentizing users of online gambling platforms in Portugal according to the tendency of these users to have compulsive gambling behavior. It also intends to evaluate the impacts of the Covid-19 pandemic on online gambling addiction by analyzing changes in user segmentation during the initial periods of the pandemic. This will be done by applying unsupervised learning algorithms, specifically K-Means and Self-Organizing Maps and by comparing user clusters from the years 2019 and 2020.Castelli, MauroPeres, Fernando Augusto JunqueiraRUNLannes, Leonardo Motta Perazzo2022-04-05T15:09:20Z2022-04-012022-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/135874TID:202988163enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:14:12Zoai:run.unl.pt:10362/135874Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:48:32.792467Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and Segmentation
title Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and Segmentation
spellingShingle Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and Segmentation
Lannes, Leonardo Motta Perazzo
Artificial Intelligence
Big Data
Clustering
Data Science
Machine Learning
Segmentation
Unsupervised Learning
title_short Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and Segmentation
title_full Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and Segmentation
title_fullStr Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and Segmentation
title_full_unstemmed Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and Segmentation
title_sort Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and Segmentation
author Lannes, Leonardo Motta Perazzo
author_facet Lannes, Leonardo Motta Perazzo
author_role author
dc.contributor.none.fl_str_mv Castelli, Mauro
Peres, Fernando Augusto Junqueira
RUN
dc.contributor.author.fl_str_mv Lannes, Leonardo Motta Perazzo
dc.subject.por.fl_str_mv Artificial Intelligence
Big Data
Clustering
Data Science
Machine Learning
Segmentation
Unsupervised Learning
topic Artificial Intelligence
Big Data
Clustering
Data Science
Machine Learning
Segmentation
Unsupervised Learning
description Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
publishDate 2022
dc.date.none.fl_str_mv 2022-04-05T15:09:20Z
2022-04-01
2022-04-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/135874
TID:202988163
url http://hdl.handle.net/10362/135874
identifier_str_mv TID:202988163
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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