Abstract

This study aims to use computational linguistics, visual analytics, and deep learning techniques to analyze hotel reviews and responses collected on TripAdvisor and to identify response strategies. To this end, we collected and analyzed 113,685 hotel reviews and responses and their semantic and syntactic relations. We are among the first to use visual analytics and deep learning-based natural language processing to empirically identify managerial responses. The empirical results indicate that our proposed multi-feature fusion, convolutional neural network model can make different types of data complement each other, thereby outperforming the comparisons. The visualization results can also be used to improve the performance of the proposed model and provide insights into response strategies, which further shows the theoretical and technical contributions of this study.

Original languageEnglish
Article number104129
JournalTourism Management
Volume80
DOIs
Publication statusPublished - Oct 2020

Keywords

  • Convolutional neural network
  • Deep learning
  • Hospitality
  • Natural language processing
  • Tourism
  • Visual analytics

ASJC Scopus subject areas

  • Development
  • Transportation
  • Tourism, Leisure and Hospitality Management
  • Strategy and Management

Fingerprint Dive into the research topics of 'Using deep learning and visual analytics to explore hotel reviews and responses'. Together they form a unique fingerprint.

  • Cite this