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Way too sentimental? a credible model for online reviews

Author

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  • Wei-Lun Chang

    (Tamkang University)

  • Yi-Pei Chen

    (Tamkang University)

Abstract

Online reviews and word of mouth are crucial to consumers. We proposed a model on the basis of a sentiment analysis in terms of positive and negative words and the concept of credibility of reviewers. This study used TripAdvisor to examine the proposed model and selected 10 out of 271 hotels in Las Vegas between January and February 2015. We also collected 116 samples around world to prove the feasibility and validity. Through sentiment analysis, we determined that the overall ranking of the 10 hotels decreased. The credibility factor has a higher influence on hotel ranking than the sentiment analysis does. These results revealed that negative emotions and low-credibility reviews have a high influence on hotel ranking. The findings from participants also confirmed emotional text in review title and content and credibility of reviewer are important for adjusting original rating.

Suggested Citation

  • Wei-Lun Chang & Yi-Pei Chen, 2019. "Way too sentimental? a credible model for online reviews," Information Systems Frontiers, Springer, vol. 21(2), pages 453-468, April.
    • Handle: RePEc:spr:infosf:v:21:y:2019:i:2:d:10.1007_s10796-017-9757-z
    DOI: 10.1007/s10796-017-9757-z
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    8. A. Geethapriya & S. Valli, 2021. "An Enhanced Approach to Map Domain-Specific Words in Cross-Domain Sentiment Analysis," Information Systems Frontiers, Springer, vol. 23(3), pages 791-805, June.
    9. Arpan Kumar Kar, 2021. "What Affects Usage Satisfaction in Mobile Payments? Modelling User Generated Content to Develop the “Digital Service Usage Satisfaction Model”," Information Systems Frontiers, Springer, vol. 23(5), pages 1341-1361, September.
    10. Franco Arolfo & Kevin Cortés Rodriguez & Alejandro Vaisman, 2022. "Analyzing the Quality of Twitter Data Streams," Information Systems Frontiers, Springer, vol. 24(1), pages 349-369, February.
    11. Arpan Kumar Kar & Sunil Kumar & P. Vigneswara Ilavarasan, 2021. "Modelling the Service Experience Encounters Using User-Generated Content: A Text Mining Approach," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 22(4), pages 267-288, December.
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