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：生成模型（如GPT）的最新进展可能以更低成本制造难以辨别的虚假客户评论，从而对社交媒体平台检测这类机器生成的虚假评论构成挑战。我们提议利用Yelp验证的高质量精英餐厅评论来生成由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，以预测显著优于现有解决方案的虚假评论。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实施检测系统来过滤可疑评论，但它们始终面临机器生成虚假评论的挑战。