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Improving trust in online reviews: a machine learning approach to detecting artificial intelligence-generated reviews

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  • Ana Marta Santos

    (Universidade Nova de Lisboa)

  • Nuno Antonio

    (Universidade Nova de Lisboa
    Universidade do Algarve)

Abstract

In the hotel industry, social reputation is critical. Consumers increasingly rely on online reviews for accommodation decisions, making Artificial Intelligence (AI) generated fraudulent reviews a significant threat. Distinguishing between genuine and AI-generated reviews is essential for hotels to maintain credibility. This study creates a unique dataset of AI-generated reviews and combines vectorization methods with text-based features to build a Machine Learning model for identifying non-genuine reviews. Results show that incorporating text-based features significantly improves detection accuracy, and simpler vectorization methods can be effective for simpler datasets. This study contributes to academia by providing a novel methodology and publicly available dataset for further research, and to the hotel industry by enhancing credibility and consumer trust through better review filtering.

Suggested Citation

  • Ana Marta Santos & Nuno Antonio, 2025. "Improving trust in online reviews: a machine learning approach to detecting artificial intelligence-generated reviews," Information Technology & Tourism, Springer, vol. 27(3), pages 739-766, September.
    • Handle: RePEc:spr:infott:v:27:y:2025:i:3:d:10.1007_s40558-025-00329-z
    DOI: 10.1007/s40558-025-00329-z
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