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

Author

Listed:
  • Enrique Bigne

    (University of Valencia)

  • Carla Ruiz

    (University of Valencia)

  • Carmen Perez-Cabañero

    (University of Valencia)

  • Antonio Cuenca

    (University of Valencia)

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.

Suggested Citation

  • Enrique Bigne & Carla Ruiz & Carmen Perez-Cabañero & Antonio Cuenca, 2023. "Are customer star ratings and sentiments aligned? A deep learning study of the customer service experience in tourism destinations," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 281-314, March.
    • Handle: RePEc:spr:svcbiz:v:17:y:2023:i:1:d:10.1007_s11628-023-00524-0
    DOI: 10.1007/s11628-023-00524-0
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    References listed on IDEAS

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