The Voice of the Guests: Analysing Airbnb Reviews as a Representative Source for Tourism Studies

User-generated content on social media has led to a new form of communication known as electronic word of mouth, which generates millions of comments about goods and services on the internet every day. This openly accessible content is crucial for prospective consumers as it helps in decision-making...

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Detalles Bibliográficos
Autores: Marti-Ochoa, Julia, Martín Fuentes, Eva, Ferrer Rosell, Berta
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/466193
Acceso en línea:https://doi.org/10.3145/epi.2024.0202
https://hdl.handle.net/10459.1/466193
Access Level:acceso abierto
Palabra clave:Online Reviews
Airbnb
Representativeness
Electronic Word of Mouth (eWom)
User-generated Content (UGC)
Sentiment Analysis
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spelling The Voice of the Guests: Analysing Airbnb Reviews as a Representative Source for Tourism StudiesMarti-Ochoa, JuliaMartín Fuentes, EvaFerrer Rosell, BertaOnline ReviewsAirbnbRepresentativenessElectronic Word of Mouth (eWom)User-generated Content (UGC)Sentiment AnalysisUser-generated content on social media has led to a new form of communication known as electronic word of mouth, which generates millions of comments about goods and services on the internet every day. This openly accessible content is crucial for prospective consumers as it helps in decision-making, but it is also valuable for product or service providers, as it allows them to improve their businesses based on user reviews, some of which are highly detailed. Another interest group that benefits from these comments are researchers and academics, as it allows them to obtain and analyse information for their studies at a relatively low cost in terms of time and money. The present study aims to perform a sentiment analysis of comments posted by guests staying at a property offered by Airbnb to determine whether their opinions about their experience are positive or negative. However, before doing so, it is necessary to find out the percentage of people who write a review about the service received on Airbnb to verify the representativeness of the reviews on this platform. To achieve this, thousands of comments posted in one year on Airbnb for the four most touristic cities in Spain are analysed: Madrid, Barcelona, Seville, and Valencia. The results show that opinions on Airbnb are much more representative compared to other platforms, as a very high participation rate is calculated. Furthermore, these opinions are predominantly positive, indicating a high level of satisfaction with the service provided.Spanish Ministry of Industry, Trade and Tourism, funded by the European Union – Next Generation EU, within the GASTROTUR project [Ref: TUR-RETOS2022-017] “Revalorización de los destinos a través de los aspectos semióticos de la imagen gastronómica y del contenido generado por los turistas” (Revaluation of destinations through the semiotic aspects of the gastronomic image and the content generated by tourists). -Spanish Ministry of Science and Innovation within the RevTour project [Ref: PID2022-138564OA-I00] “Uso de las reseñas en línea para la inteligencia turística y el establecimiento de estándares de evaluación transparentes y confiables” (Use of online reviews for tourism intelligence and for the establishment of transparent and reliable evaluation standards). -Project TradiTur [Grant Id. TED2021-129763B-I00] “Retos para la transición digital en turismo: análisis de la inteligencia turística y propuestas normativas” (Challenges for the digital transition in tourism: analysis of tourism intelligence and regulatory proposals), and finally the Institute of Social and Territorial Development within the ResTur project for the 2023CRINDESTABC callEPI SCP2024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://doi.org/10.3145/epi.2024.0202https://hdl.handle.net/10459.1/466193reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)Inglésinfo:eu-repo/grantAgreement/AEI//PID2022-138564OA-I00Reproducció del document publicat a https://doi.org/10.3145/epi.2024.0202Profesional de la información, 2024, vol. 33, núm. 2, e330202cc-by (c) Júlia Martí-Ochoa, Eva Martín-Fuentes, Berta Ferrer-Rosell, 2024Attribution 4.0 Internationalinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:repositori.udl.cat:10459.1/4661932026-06-24T12:42:17Z
dc.title.none.fl_str_mv The Voice of the Guests: Analysing Airbnb Reviews as a Representative Source for Tourism Studies
title The Voice of the Guests: Analysing Airbnb Reviews as a Representative Source for Tourism Studies
spellingShingle The Voice of the Guests: Analysing Airbnb Reviews as a Representative Source for Tourism Studies
Marti-Ochoa, Julia
Online Reviews
Airbnb
Representativeness
Electronic Word of Mouth (eWom)
User-generated Content (UGC)
Sentiment Analysis
title_short The Voice of the Guests: Analysing Airbnb Reviews as a Representative Source for Tourism Studies
title_full The Voice of the Guests: Analysing Airbnb Reviews as a Representative Source for Tourism Studies
title_fullStr The Voice of the Guests: Analysing Airbnb Reviews as a Representative Source for Tourism Studies
title_full_unstemmed The Voice of the Guests: Analysing Airbnb Reviews as a Representative Source for Tourism Studies
title_sort The Voice of the Guests: Analysing Airbnb Reviews as a Representative Source for Tourism Studies
dc.creator.none.fl_str_mv Marti-Ochoa, Julia
Martín Fuentes, Eva
Ferrer Rosell, Berta
author Marti-Ochoa, Julia
author_facet Marti-Ochoa, Julia
Martín Fuentes, Eva
Ferrer Rosell, Berta
author_role author
author2 Martín Fuentes, Eva
Ferrer Rosell, Berta
author2_role author
author
dc.subject.none.fl_str_mv Online Reviews
Airbnb
Representativeness
Electronic Word of Mouth (eWom)
User-generated Content (UGC)
Sentiment Analysis
topic Online Reviews
Airbnb
Representativeness
Electronic Word of Mouth (eWom)
User-generated Content (UGC)
Sentiment Analysis
description User-generated content on social media has led to a new form of communication known as electronic word of mouth, which generates millions of comments about goods and services on the internet every day. This openly accessible content is crucial for prospective consumers as it helps in decision-making, but it is also valuable for product or service providers, as it allows them to improve their businesses based on user reviews, some of which are highly detailed. Another interest group that benefits from these comments are researchers and academics, as it allows them to obtain and analyse information for their studies at a relatively low cost in terms of time and money. The present study aims to perform a sentiment analysis of comments posted by guests staying at a property offered by Airbnb to determine whether their opinions about their experience are positive or negative. However, before doing so, it is necessary to find out the percentage of people who write a review about the service received on Airbnb to verify the representativeness of the reviews on this platform. To achieve this, thousands of comments posted in one year on Airbnb for the four most touristic cities in Spain are analysed: Madrid, Barcelona, Seville, and Valencia. The results show that opinions on Airbnb are much more representative compared to other platforms, as a very high participation rate is calculated. Furthermore, these opinions are predominantly positive, indicating a high level of satisfaction with the service provided.
publishDate 2024
dc.date.none.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.3145/epi.2024.0202
https://hdl.handle.net/10459.1/466193
url https://doi.org/10.3145/epi.2024.0202
https://hdl.handle.net/10459.1/466193
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/AEI//PID2022-138564OA-I00
Reproducció del document publicat a https://doi.org/10.3145/epi.2024.0202
Profesional de la información, 2024, vol. 33, núm. 2, e330202
dc.rights.none.fl_str_mv cc-by (c) Júlia Martí-Ochoa, Eva Martín-Fuentes, Berta Ferrer-Rosell, 2024
Attribution 4.0 International
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv cc-by (c) Júlia Martí-Ochoa, Eva Martín-Fuentes, Berta Ferrer-Rosell, 2024
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv EPI SCP
publisher.none.fl_str_mv EPI SCP
dc.source.none.fl_str_mv reponame:Repositori Obert UdL
instname:Universitat de Lleida (UdL)
instname_str Universitat de Lleida (UdL)
reponame_str Repositori Obert UdL
collection Repositori Obert UdL
repository.name.fl_str_mv
repository.mail.fl_str_mv
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