Recent advances in generative models such as GPT may be used to fabricate indistinguishable fake customer reviews at a much lower cost, thus posing challenges for social media platforms to detect these machine-generated fake reviews. We propose to leverage the high-quality elite restaurant reviews verified by Yelp to generate fake reviews from the OpenAI GPT review creator and ultimately fine-tune a GPT output detector to predict fake reviews that significantly outperform existing solutions. We further apply the model to predict non-elite reviews and identify the patterns across several dimensions, such as review, user and restaurant characteristics, and writing style. We show that social media platforms are continuously challenged by machine-generated fake reviews, although they may implement detection systems to filter out suspicious reviews.

翻译：生成式模型（如GPT）的最新进展可能被用于以极低代价制造难以区分的虚假客户评论，从而给社交媒体平台检测这些机器生成的虚假评论带来挑战。我们提出利用Yelp验证的高质量精英餐厅评论来生成OpenAI GPT评论生成器制造的虚假评论，并最终微调一个GPT输出检测器，以预测虚假评论，其性能显著优于现有解决方案。我们进一步将模型应用于预测非精英评论，并从评论、用户和餐厅特征以及写作风格等多个维度识别模式。研究表明，尽管社交媒体平台可能部署检测系统来过滤可疑评论，但机器生成的虚假评论仍持续对其构成挑战。