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

Ana Marta Santos () and Nuno Antonio ()
Additional contact information
Ana Marta Santos: Universidade Nova de Lisboa
Nuno Antonio: Universidade Nova de Lisboa

Information Technology & Tourism, 2025, vol. 27, issue 3, No 9, 739-766

Abstract: 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.

Keywords: Fraudulent reviews; AI-generated; Natural Language processing; Machine learning; Vectorization methods (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s40558-025-00329-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infott:v:27:y:2025:i:3:d:10.1007_s40558-025-00329-z

Ordering information: This journal article can be ordered from
http://www.springer. ... ystems/journal/40558

DOI: 10.1007/s40558-025-00329-z

Access Statistics for this article

Information Technology & Tourism is currently edited by Zheng Xiang

More articles in Information Technology & Tourism from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().