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...
| Autores: | , , |
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| 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) |
| Sumario: | 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. |
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