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：近年来，像GPT这样的生成模型可以用于制造难以区别的虚假客户评论，造成社交媒体平台检测这些机器生成的虚假评论所面临的挑战更加严峻。本文提出了利用Yelp验证的高质量精品餐厅评论来生成OpenAI GPT评论生成程序的虚假评论，并最终对GPT输出检测器进行微调，以预测比现有解决方案更为准确的虚假评论。我们进一步将该模型应用于预测非精品评论，并识别几个维度（如评论、用户和餐厅特征以及写作风格）上的模式。我们展示了社交媒体平台不断受到机器生成虚假评论的挑战尽管它们可能实施检测系统来过滤可疑评论。
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