Are customer star ratings and sentiments aligned? A deep learning study of the customer service experience in tourism destinations

Enrique Bigne (), Carla Ruiz (), Carmen Perez-Cabañero () and Antonio Cuenca ()
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Enrique Bigne: University of Valencia
Carla Ruiz: University of Valencia
Carmen Perez-Cabañero: University of Valencia
Antonio Cuenca: University of Valencia

Service Business, 2023, vol. 17, issue 1, No 12, 314 pages

Abstract: Abstract This study explores the consistency between star ratings and sentiments expressed in online reviews and how they relate to the different components of the customer experience. We combine deep learning applied to natural language processing, machine learning and artificial neural networks to identify how the positive and negative components of 20,954 online reviews posted on TripAdvisor about tourism attractions in Venice impact on their overall polarity and star ratings. Our findings showed that sentiment valence is aligned with star ratings. A cancel-out effect operates between the positive and negative sentiments linked to the service experience dimensions in mixed-neutral reviews.

Keywords: Sentiment analysis; Deep learning; Artificial neural networks; Tourism destination; Star rating (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11628-023-00524-0

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