Do travelers' reviews depend on the destination? An analysis in coastal and urban peer‐to‐peer lodgings

By Manuel J. Sánchez-Franco, Manuel Rey-Moreno. Psychology & Marketing, 2021

87 citations recorded by the source corpus.

Our research applies a service, feature ‐ oriented approach to deeply explore the subjective experiences shared publicly by Airbnb guests in their reviews. Our processed data set contains 73,557 reviews of Airbnb stays in coastal and urban destinations between 2017 and 2020. A topic modeling based on the BERTopic approach is applied to detect dense clusters of reviews and identify one highly relevant and interpretable topic per cluster related to core and essential sharing services and surrounding features. Our study, therefore, allows a higher understanding of the relationships between urban versus coastal destinations and guests' preferences. Furthermore, it enables hosts to differentiate the touristic short ‐ rentals lodgings according to customer experiences

Subfields: Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/7406c744b88c6695b7f55be5ed8ec338d073e7d4

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1. Roman Egger
2. Joanne Yu

Citations in the corpus

• A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts (2022, background): “Regardless of the popularity of LDA within the social science branch, its efficacy in analyzing social media data has been highly criticized (Egger and Yu, 2021; Sánchez-Franco and Rey-Moreno, 2022).”