Detecting and Understanding Textual Deepfakes in Online Reviews
Open accessAbstract
Deepfakes endanger business and society. Regarding fraudulent texts created with deep learning techniques, this may become particularly evident for online reviews. Here, customers naturally rely on truthful information about a product or service to adequately evaluate its worthiness. However, in the light of the proliferation of deepfakes, customers may increasingly harbour distrust and thereby affect a retailers business. To counteract this, we propose a novel IT artifact capable of detecting textual deepfakes to then explain their peculiarities by using explainable artificial intelligence. Finally, we demonstrate the utility of such explanations for the case of online reviews in e-commerce.
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Kowalczyk et al. detected GPT-2-generated fake reviews using Shapley Additive Explanations (SHAP).
“For instance, Kowalczyk et al. [2022] detected GPT-2-generated fake reviews using Shapley Additive Explanations (SHAP) [Lundberg and Lee, 2017].”
From Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges (2025) · cites this paper as Kowalczyk et al., 2022
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- Authors
- Kowalczyk, P., Röder, M., Dürr, A., & Thiesse, F.
- Affiliations
- University of Würzburg (DE)
- Venue
- Proceedings of the Annual Hawaii International Conference on System Sciences
- Published
- 2022
- ISSN
- 1530-1605 (ISSN-L)
- 2572-6862
- OpenAlex
- W4205705588
- Cited by
- 9
- References
- 47
- Citations by year
- 2026: 1 · 2024: 4 · 2023: 3 · 2022: 1
- FWCI
- 1.79
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Hawaii International Conference on System Sciences (HICSS) (publishedVersion, cc-by-nc-nd)
- Journal of the Association for Information Systems (submittedVersion)
- ScholarSpace (University of Hawaii at Manoa) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Physical Sciences › Computer Science › Artificial Intelligence › Authorship Attribution and Profiling
- Keywords
- deepfakes, online reviews, explainable AI, e-commerce, consumer trust, text forgery detection
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