Assessing the helpfulness of online hotel reviews: A classification-based approach

Pei Ju Lee, Ya Han Hu, Kuan Ting Lu

Research output: Contribution to journalArticlepeer-review

78 Scopus citations

Abstract

With the rapid development of Web 2.0, travelers have started sharing their travel experiences on websites. The expanding amount of online hotel reviews results in the problem of information overload. Therefore, the effective identification of helpful reviews has become an important research issue. In this study, online hotel reviews were collected from TripAdvisor.com, and the helpfulness of these reviews was comprehensively investigated from the aspects of review quality, review sentiment, and reviewer characteristics. Review helpfulness prediction models were also developed by using classification techniques. The results indicate that reviewer characteristics are good predictors of review helpfulness, whereas review quality and review sentiment are poor predictors of review helpfulness.

Original languageEnglish
Pages (from-to)436-445
Number of pages10
JournalTelematics and Informatics
Volume35
Issue number2
DOIs
StatePublished - May 2018

Keywords

  • Classification
  • Online hotel review
  • Review helpfulness
  • Sentiment analysis

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