A compositional analysis of emotions in Airbnb reviews: online and face-to-face experiences

With a focus on personalized travel experiences, platforms like Airbnb have revolutionized tourist interactions by offering authentic local experiences, from cooking classes with locals to city tours. This study addresses the gap in understanding emotions expressed in online versus face-to-face Airb...

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Detalles Bibliográficos
Autores: Marti-Ochoa, Julia, Ferrer Rosell, Berta, Martín Fuentes, Eva
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2025
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/468062
Acceso en línea:https://doi.org/10.1080/02508281.2025.2489439
https://hdl.handle.net/10459.1/468062
Access Level:acceso embargado
Palabra clave:UGC
eWOM
Sentiment analysis
DistilRoBERTa
Compositional Data Analysis (CoDa)
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spelling A compositional analysis of emotions in Airbnb reviews: online and face-to-face experiencesMarti-Ochoa, JuliaFerrer Rosell, BertaMartín Fuentes, EvaUGCeWOMSentiment analysisDistilRoBERTaCompositional Data Analysis (CoDa)With a focus on personalized travel experiences, platforms like Airbnb have revolutionized tourist interactions by offering authentic local experiences, from cooking classes with locals to city tours. This study addresses the gap in understanding emotions expressed in online versus face-to-face Airbnb experiences. This research utilizes the DistilRoBERTa method and compositional data analysis (CoDa) on peer-to-peer platforms. By examining Airbnb online reviews, this study utilizes sentiment analysis to quantify emotional expressions depending on the type of experiences and categories. The findings suggest that online interactions tend to produce more positive emotions like joy and surprise compared to offline settings, where a variety of emotional responses is evident. Art and Culture, Cooking, and Entertainment categories receive more reviews expressing emotions of surprise and happiness, while Wellness and Tours feature a more varied range of emotions. These methods help us understand the emotional aspects of peer-to-peer experiences, thus improving our knowledge of consumer behaviour.This work was supported by the Spanish Ministry of Science and Innovation MCIN/AEI/10.13039/501100011033/ FEDER, UE within the RevTour project ‘Use of online reviews for tourism intelligence and for the establishment of transparent and reliable evaluation standards’ (Ref:PID2022-138564OA-I00) and Institute for social and Territorial Development (INDEST) within the ResTur project for the call (2023CRINDESTABC).Taylor and Francis Group2025info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://doi.org/10.1080/02508281.2025.2489439https://hdl.handle.net/10459.1/468062reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)Inglésinfo:eu-repo/grantAgreement/AEI//PID2022-138564OA-I00Versió postprint del document publicat a https://doi.org/10.1080/02508281.2025.2489439Tourism Recreation Research, 2025, p. 1-15, In presscc-by-nc (c) Taylor and Francis Group, 2025info:eu-repo/semantics/embargoedAccesshttps://creativecommons.org/licenses/by-nc/4.0/deed.esoai:repositori.udl.cat:10459.1/4680622026-06-24T12:42:17Z
dc.title.none.fl_str_mv A compositional analysis of emotions in Airbnb reviews: online and face-to-face experiences
title A compositional analysis of emotions in Airbnb reviews: online and face-to-face experiences
spellingShingle A compositional analysis of emotions in Airbnb reviews: online and face-to-face experiences
Marti-Ochoa, Julia
UGC
eWOM
Sentiment analysis
DistilRoBERTa
Compositional Data Analysis (CoDa)
title_short A compositional analysis of emotions in Airbnb reviews: online and face-to-face experiences
title_full A compositional analysis of emotions in Airbnb reviews: online and face-to-face experiences
title_fullStr A compositional analysis of emotions in Airbnb reviews: online and face-to-face experiences
title_full_unstemmed A compositional analysis of emotions in Airbnb reviews: online and face-to-face experiences
title_sort A compositional analysis of emotions in Airbnb reviews: online and face-to-face experiences
dc.creator.none.fl_str_mv Marti-Ochoa, Julia
Ferrer Rosell, Berta
Martín Fuentes, Eva
author Marti-Ochoa, Julia
author_facet Marti-Ochoa, Julia
Ferrer Rosell, Berta
Martín Fuentes, Eva
author_role author
author2 Ferrer Rosell, Berta
Martín Fuentes, Eva
author2_role author
author
dc.subject.none.fl_str_mv UGC
eWOM
Sentiment analysis
DistilRoBERTa
Compositional Data Analysis (CoDa)
topic UGC
eWOM
Sentiment analysis
DistilRoBERTa
Compositional Data Analysis (CoDa)
description With a focus on personalized travel experiences, platforms like Airbnb have revolutionized tourist interactions by offering authentic local experiences, from cooking classes with locals to city tours. This study addresses the gap in understanding emotions expressed in online versus face-to-face Airbnb experiences. This research utilizes the DistilRoBERTa method and compositional data analysis (CoDa) on peer-to-peer platforms. By examining Airbnb online reviews, this study utilizes sentiment analysis to quantify emotional expressions depending on the type of experiences and categories. The findings suggest that online interactions tend to produce more positive emotions like joy and surprise compared to offline settings, where a variety of emotional responses is evident. Art and Culture, Cooking, and Entertainment categories receive more reviews expressing emotions of surprise and happiness, while Wellness and Tours feature a more varied range of emotions. These methods help us understand the emotional aspects of peer-to-peer experiences, thus improving our knowledge of consumer behaviour.
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1080/02508281.2025.2489439
https://hdl.handle.net/10459.1/468062
url https://doi.org/10.1080/02508281.2025.2489439
https://hdl.handle.net/10459.1/468062
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
Versió postprint del document publicat a https://doi.org/10.1080/02508281.2025.2489439
Tourism Recreation Research, 2025, p. 1-15, In press
dc.rights.none.fl_str_mv cc-by-nc (c) Taylor and Francis Group, 2025
info:eu-repo/semantics/embargoedAccess
https://creativecommons.org/licenses/by-nc/4.0/deed.es
rights_invalid_str_mv cc-by-nc (c) Taylor and Francis Group, 2025
https://creativecommons.org/licenses/by-nc/4.0/deed.es
eu_rights_str_mv embargoedAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Taylor and Francis Group
publisher.none.fl_str_mv Taylor and Francis Group
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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