Beyond the Reviews:: Unveiling the Hotel Experience Through Text Mining

• Sebastián Araya-Pizarro ^[1] ; Nando Verelst ^[2]
  1. [1] Universidad de La Serena

     Universidad de La Serena

     La Serena, Chile

     
  2. [2] Universidad Diego Portales

     Universidad Diego Portales

     Santiago, Chile

     
• Localización: RIAT: Revista Interamericana de Medioambiente y Turismo, ISSN-e 0718-235X, Vol. 20, Nº. 2, 2024, págs. 126-139
• Idioma: inglés
• Títulos paralelos:
  • Más allá de las reseñas:: Desvelando la experiencia hotelera con minería de texto
• Enlaces
  • Texto completo
• Resumen
  • español

    En la gestión hotelera, es crucial comprender los factores que resultan esenciales para la satisfacción y fidelización de los clientes. Este estudio tiene como objetivo determinar los atributos que influyen en las experiencias de los turistas que hospedan en hoteles de Santiago, Chile. La metodología consiste en técnicas de minería de textos, análisis de senti¬mientos y regresiones logísticas binarias para analizar 1,467 reseñas en línea de 10 hoteles extraídas desde la plataforma Booking.com. Los resultados destacan que los comentarios se concentran en la infraestructura, ubicación, comida y per¬sonal, con sentimientos similares. Además, se halló que la probabilidad de una experiencia positiva aumenta significati¬vamente cuando la localización, las amenidades y la relación precio-calidad son adecuadas. Se concluye que la minería de datos y el análisis de sentimientos son herramientas efecti¬vas para comprender los atributos clave de la experiencia hotelera, cuya gestión mejorada podría aumentar sustancial¬mente la satisfacción y la lealtad de los turistas.

  • English

    In hotel management, it is crucial to understand the fac¬tors that are essential to customer satisfaction and loyalty. This study aims to determine the attributes influencing tourist experiences in hotels in Santiago, Chile. The me¬thodology consists of text mining, sentiment analysis, and binary logistic regressions were employed to analyze 1,467 online reviews from 10 hotels extracted from the Booking.com platform. Results highlight those comments on infrastructure, location, food, and staff, with similar sentiments. Additionally, it was found that the likelihood of a positive experience significantly increases when lo¬cation, amenities, and price-quality ratio are adequate. It is concluded that data mining and sentiment analysis are practical tools to comprehend key attributes of the hotel experience, whose enhanced management could subs¬tantially enhance guest satisfaction and loyalty.

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