Using deep learning and visual analytics to explore hotel reviews and responses

Yung Chun Chang, Chih Hao Ku, Chien Hung Chen

研究成果: 雜誌貢獻文章同行評審

60 引文 斯高帕斯(Scopus)


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.

期刊Tourism Management
出版狀態已發佈 - 10月 2020

ASJC Scopus subject areas

  • 發展
  • 運輸
  • 旅遊、休閒和酒店管理
  • 策略與管理


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