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From reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisor

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Resumo:Over the past decade, sentiment analysis has emerged as a pivotal tool in tourism-related texts, driven by the sheer volume of tourist attractions and the wealth of online information. Tourists increasingly turn to travel websites to access specific information that often eludes standard evaluations of tourist attractions. Forums particularly illuminate specific information needs and their ties to potential destinations. Among these platforms, TripAdvisor has become a favoured choice for posting reviews, ratings, and facilitating online bookings. In this context, this study aims to analyse and assess sentiment in reviews sourced from the online platform TripAdvisor, focusing on tourist attractions in the northern Portuguese destination of Bragança. The research spotlights the disparity between qualitative and quantitative rankings. The study also underscores the importance of data pre-processing, including removing irrelevant information and stop words. Pre-processing was crucial in refining sentiment prediction accuracy, highlighting the differentiated roles of these words in context and meaning. Despite utilising advanced techniques such as tokenisation, TF-IDF weighting, logistic regression, and n-grams, the study‘s models encountered challenges in achieving high accuracy in sentiment prediction. Even the incorporation of bigrams did not yield substantial performance improvements, with the models frequently inclined to overestimate negative and positive sentiments.
Autores principais:Scalabrini, E.C.B.
Outros Autores:Ferreira, Jessica; Fernandes, Paula Odete; Moraes, Thiago
Assunto:Qualitative reviews Quantitative ranking Sentimental analysis TripAdvisor Reviews
Ano:2024
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
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author Scalabrini, E.C.B.
author2 Ferreira, Jessica
Fernandes, Paula Odete
Moraes, Thiago
author2_role author
author
author
author_facet Scalabrini, E.C.B.
Ferreira, Jessica
Fernandes, Paula Odete
Moraes, Thiago
author_role author
contributor_name_str_mv Biblioteca Digital do IPB
country_str PT
creators_json_txt [{\"Person.name\":\"Scalabrini, E.C.B.\",\"Person.identifier.orcid\":\"0000-0001-7164-2471\"},{\"Person.name\":\"Ferreira, Jessica\",\"Person.identifier.orcid\":\"0000-0002-4141-6702\"},{\"Person.name\":\"Fernandes, Paula Odete\",\"Person.identifier.orcid\":\"0000-0001-8714-4901\"},{\"Person.name\":\"Moraes, Thiago\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Biblioteca Digital do IPB
datacite.creators.creator.creatorName.fl_str_mv Scalabrini, E.C.B.
Ferreira, Jessica
Fernandes, Paula Odete
Moraes, Thiago
datacite.date.Accepted.fl_str_mv 2024-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2025-01-29T14:13:31Z
datacite.date.embargoed.fl_str_mv 2025-01-29T14:13:31Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Qualitative reviews
Quantitative ranking
Sentimental analysis
TripAdvisor
Reviews
datacite.titles.title.fl_str_mv From reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisor
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.creator.none.fl_str_mv Scalabrini, E.C.B.
Ferreira, Jessica
Fernandes, Paula Odete
Moraes, Thiago
dc.date.Accepted.fl_str_mv 2024-01-01T00:00:00Z
dc.date.available.fl_str_mv 2025-01-29T14:13:31Z
dc.date.embargoed.fl_str_mv 2025-01-29T14:13:31Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10198/31092
dc.language.none.fl_str_mv eng
dc.publisher.none.fl_str_mv De Gruyter Poland
dc.rights.cclincense.fl_str_mv http://creativecommons.org/licenses/by/4.0/
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Qualitative reviews
Quantitative ranking
Sentimental analysis
TripAdvisor
Reviews
dc.title.fl_str_mv From reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisor
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
description Over the past decade, sentiment analysis has emerged as a pivotal tool in tourism-related texts, driven by the sheer volume of tourist attractions and the wealth of online information. Tourists increasingly turn to travel websites to access specific information that often eludes standard evaluations of tourist attractions. Forums particularly illuminate specific information needs and their ties to potential destinations. Among these platforms, TripAdvisor has become a favoured choice for posting reviews, ratings, and facilitating online bookings. In this context, this study aims to analyse and assess sentiment in reviews sourced from the online platform TripAdvisor, focusing on tourist attractions in the northern Portuguese destination of Bragança. The research spotlights the disparity between qualitative and quantitative rankings. The study also underscores the importance of data pre-processing, including removing irrelevant information and stop words. Pre-processing was crucial in refining sentiment prediction accuracy, highlighting the differentiated roles of these words in context and meaning. Despite utilising advanced techniques such as tokenisation, TF-IDF weighting, logistic regression, and n-grams, the study‘s models encountered challenges in achieving high accuracy in sentiment prediction. Even the incorporation of bigrams did not yield substantial performance improvements, with the models frequently inclined to overestimate negative and positive sentiments.
dirty 0
eu_rights_str_mv openAccess
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funding.funder.alternateName_str_mv FCT
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funding.funder.identifier_str_mv http://doi.org/10.13039/501100001871
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funding.funder.name_str_mv Fundação para a Ciência e a Tecnologia
Fundação para a Ciência e a Tecnologia
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6817 - DCRRNI ID
id ipb_7d2bef9d58c2de192c0a0df61fb1c0ab
identifier.url.fl_str_mv http://hdl.handle.net/10198/31092
instacron_str ipb
institution Instituto Politécnico de Bragança
instname_str Instituto Politécnico de Bragança
language eng
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network_name_str Biblioteca Digital do IPB
oai_identifier_str oai:bibliotecadigital.ipb.pt:10198/31092
organization_str_mv urn:organizationAcronym:ipb
person_str_mv Scalabrini, E.C.B.
Scalabrini, E.C.B.
https://www.ciencia-id.pt/C215-238E-B5E1
C215-238E-B5E1
http://orcid.org/0000-0001-7164-2471
0000-0001-7164-2471
Ferreira, Jessica
Ferreira, Jessica
https://www.ciencia-id.pt/7A15-9500-44E4
7A15-9500-44E4
http://orcid.org/0000-0002-4141-6702
0000-0002-4141-6702
Fernandes, Paula Odete
Fernandes, Paula Odete
https://www.ciencia-id.pt/991D-9D1E-D67D
991D-9D1E-D67D
http://orcid.org/0000-0001-8714-4901
0000-0001-8714-4901
Moraes, Thiago
publishDate 2024
publisher.none.fl_str_mv De Gruyter Poland
reponame_str Biblioteca Digital do IPB
repository_id_str urn:repositoryAcronym:ipb
service_str_mv urn:repositoryAcronym:ipb
spelling engDe Gruyter Polandpt_PTOver the past decade, sentiment analysis has emerged as a pivotal tool in tourism-related texts, driven by the sheer volume of tourist attractions and the wealth of online information. Tourists increasingly turn to travel websites to access specific information that often eludes standard evaluations of tourist attractions. Forums particularly illuminate specific information needs and their ties to potential destinations. Among these platforms, TripAdvisor has become a favoured choice for posting reviews, ratings, and facilitating online bookings. In this context, this study aims to analyse and assess sentiment in reviews sourced from the online platform TripAdvisor, focusing on tourist attractions in the northern Portuguese destination of Bragança. The research spotlights the disparity between qualitative and quantitative rankings. The study also underscores the importance of data pre-processing, including removing irrelevant information and stop words. Pre-processing was crucial in refining sentiment prediction accuracy, highlighting the differentiated roles of these words in context and meaning. Despite utilising advanced techniques such as tokenisation, TF-IDF weighting, logistic regression, and n-grams, the study‘s models encountered challenges in achieving high accuracy in sentiment prediction. Even the incorporation of bigrams did not yield substantial performance improvements, with the models frequently inclined to overestimate negative and positive sentiments.application/pdfpt_PTFrom reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisorPersonalScalabrini, E.C.B.DSpacehttp://dspace.org/items/1b00625e-3454-47d8-8ab5-016f90c9d7e2DSpacehttp://dspace.org/items/1b00625e-3454-47d8-8ab5-016f90c9d7e2ScalabriniElaine C.B.Ciência IDhttps://www.ciencia-id.ptC215-238E-B5E1ORCIDhttp://orcid.org0000-0001-7164-2471Scopus Author IDhttps://www.scopus.com57219651339PersonalFerreira, JessicaDSpacehttp://dspace.org/items/62d87d26-8945-41ec-bc3a-cf618fd3f2fcDSpacehttp://dspace.org/items/62d87d26-8945-41ec-bc3a-cf618fd3f2fcFerreiraJessicaCiência IDhttps://www.ciencia-id.pt7A15-9500-44E4ORCIDhttp://orcid.org0000-0002-4141-6702Scopus Author IDhttps://www.scopus.com57204795793PersonalFernandes, Paula OdeteDSpacehttp://dspace.org/items/2269147c-2b53-4d1c-bc1b-f1367d197262DSpacehttp://dspace.org/items/2269147c-2b53-4d1c-bc1b-f1367d197262FernandesPaula OdeteCiência IDhttps://www.ciencia-id.pt991D-9D1E-D67DORCIDhttp://orcid.org0000-0001-8714-4901Scopus Author IDhttps://www.scopus.com35200741800Moraes, ThiagoHostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptISSNIsPartOf2182-4924DOIIsPartOf10.2478/ejthr-2024-00222025-01-29T14:13:31Z20242024-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/31092http://purl.org/coar/access_right/c_abf2open accessQualitative reviewsQuantitative rankingSentimental analysisTripAdvisorReviews1635741 bytesFundação para a Ciência e a TecnologiaApplied Management Research Unit6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaApplied Management Research Unit6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871literaturehttp://purl.org/coar/resource_type/c_6501journal article2024http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/c4c034a2-e785-4ff4-882e-670ecdf82f3f/downloadEuropean Journal of Tourism, Hospitality and Recreation142299311
spellingShingle From reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisor
Scalabrini, E.C.B.
Qualitative reviews
Quantitative ranking
Sentimental analysis
TripAdvisor
Reviews
status SINGLETON
subject.fl_str_mv Qualitative reviews
Quantitative ranking
Sentimental analysis
TripAdvisor
Reviews
title From reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisor
title_full From reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisor
title_fullStr From reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisor
title_full_unstemmed From reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisor
title_short From reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisor
title_sort From reviews to emotions: analysing Bragança’s tourism attractions on TripAdvisor
topic Qualitative reviews
Quantitative ranking
Sentimental analysis
TripAdvisor
Reviews
topic_facet Qualitative reviews
Quantitative ranking
Sentimental analysis
TripAdvisor
Reviews
url http://hdl.handle.net/10198/31092
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