Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Ana Catarina Guinote Fernandes Alves
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/127908
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing Intelligence
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spelling Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distributionAirbnbText MiningOnline ReviewsSocial NormsMarket NormsDissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceThis thesis aims to perform a holistic investigation concerning how Airbnb accommodation features and hosts’ attributes influence guest’s reviews and how are the main topics distributed. A dataset containing almost 4 million reviews from major touristic cities in the world (Milan, Lisbon, Amsterdam, Toronto, San-Francisco, and Sydney) was used for the text mining analysis to uncover the reviews’ social and market norms, as well as the guests’ sentiments and topics distribution. This research uses both Mallet LDA (Latent Dirichlet Allocation) and Word2Vec methods to unveil the semantic structure and similarity between data in this study. This approach will allow hospitality providers to understand the impact of underlying factors on reviewers’ opinions for further improvement of their services. Finally, this study develops a predictive unbiased model to forecast the review’s scores, with an accuracy of 90.70%.Pinto, Diego CostaRUNRodrigues, Ana Catarina Guinote Fernandes Alves2021-11-18T14:51:09Z2021-11-082021-11-08T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/127908TID:202791106enginfo: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:RCAAP2024-03-11T05:07:42Zoai:run.unl.pt:10362/127908Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:46:13.872346Repositório 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 Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution
title Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution
spellingShingle Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution
Rodrigues, Ana Catarina Guinote Fernandes Alves
Airbnb
Text Mining
Online Reviews
Social Norms
Market Norms
title_short Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution
title_full Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution
title_fullStr Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution
title_full_unstemmed Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution
title_sort Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution
author Rodrigues, Ana Catarina Guinote Fernandes Alves
author_facet Rodrigues, Ana Catarina Guinote Fernandes Alves
author_role author
dc.contributor.none.fl_str_mv Pinto, Diego Costa
RUN
dc.contributor.author.fl_str_mv Rodrigues, Ana Catarina Guinote Fernandes Alves
dc.subject.por.fl_str_mv Airbnb
Text Mining
Online Reviews
Social Norms
Market Norms
topic Airbnb
Text Mining
Online Reviews
Social Norms
Market Norms
description Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing Intelligence
publishDate 2021
dc.date.none.fl_str_mv 2021-11-18T14:51:09Z
2021-11-08
2021-11-08T00:00:00Z
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/10362/127908
TID:202791106
url http://hdl.handle.net/10362/127908
identifier_str_mv TID:202791106
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
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repository.mail.fl_str_mv
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