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：近来生成模型（如GPT）的快速发展使得制造虚假的顾客评论变得十分低成本，从而让社交媒体平台更难检测这些由机器生成的虚假评论。我们提出利用Yelp验证的高质量精英餐厅评论来制造OpenAI GPT评论生成器中的伪评论，最终对GPT输出检测器进行微调以预测远胜现有各种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识别跨多个维度的模式，例如评论、用户和餐厅特征以及写作风格。我们证明社交媒体平台一直在面临机器生成的虚假评论的挑战，尽管它们可能实施检测系统来过滤可疑评论。
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