Tourism Reputation Index for Assessing Perceptions on Destinations Using Collaborative Text Data

  1. Paula Antón Maraña 1
  2. Bruno Baruque Zanón 2
  3. Santiago Porras Alfonso 1
  4. Pablo Arranz Val 1
  1. 1 Department of Applied Economics, UNIVERSITY OF BURGOS, SPAIN
  2. 2 Department of Computer Engineering, UNIVERSITY OF BURGOS, SPAIN
Revista:
Estudios de economía aplicada

ISSN: 1133-3197,  1697-5731

Año de publicación: 2023

Título del ejemplar: Ciencia de datos para la Economía Aplicada

Volumen: 41

Número: 1

Tipo: Artículo

DOI: 10.25115/SAE.V41I1.9076 DIALNET GOOGLE SCHOLAR

Otras publicaciones en: Estudios de economía aplicada

Resumen

El sector turístico está experimentando un cambio de tendencia ante el uso generalizado de la Web 2.0. por parte de los turistas. Este fenómeno ha impulsado a los agentes turísticos a aplicar técnicas Big Data y herramientas de Inteligencia de Negocio a la hora de conocer qué piensan y qué desean a los turistas. En este sentido, toma especial relevancia el análisis del Electronic Word Of Mouth en las Redes Sociales, y la literatura académica ha encontrado algunas dificultades al extraer datos, determinar su significado y vincularlo con el destino. El objetivo de este trabajo es presentar los resultados que se pueden obtener con el diseño de un índice reputacional turístico, por medio del análisis de los datos creados de manera colaborativa en la Red Social de Twitter. Para ello, se ha creado una herramienta de IN que permite extraer datos de los mensajes cortos de texto publicados por los usuarios (tweets) y procesarlos mediante la implementación de un proceso de Extract, Transform and Load. En este proceso, se realiza un Procesamiento del Lenguaje Natural, centrado en tareas de Análisis de Sentimientos, aplicando un modelo de clasificación automática (Multinomial Naive Bayes) y, seguidamente, una categorización temática automática de estos textos en función de los términos que contengan. Posteriormente, se analizan los datos, calculando un índice de reputación online global a partir de subíndices de percepción sobre diferentes aspectos turísticos. Estos índices se muestran a los usuarios mediante un cuadro de mando interactivo, que permite comparar entre diferentes consultas asociadas a una localidad turística y a un periodo temporal. Este trabajo contribuye a que los agentes turísticos conozcan la percepción sobre los destinos y tomen decisiones adecuadas e informadas en tiempo real, facilitando una gestión inteligente de los datos que permita crear destinos turísticos inteligentes con ventajas competitivas, únicas y sostenibles.

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Fuente de los datos: Dialnet