The increasing popularity of online review systems motivates malevolent intent in competing sellers and service providers to manipulate consumers by fabricating product/service reviews. Immoral actors use Sybil accounts, bot farms, and purchase authentic accounts to promote products and vilify competitors. Facing the continuous advancement of review spamming techniques, the research community should step back, assess the approaches explored to date to combat fake reviews, and regroup to define new ones. This paper reviews the literature on Fake Review Detection (FRD) on online platforms. It covers both basic research and commercial solutions, and discusses the reasons behind the limited level of success that the current approaches and regulations have had in preventing damage due to deceptive reviews.

在线评论系统的日益流行激发了竞争卖家和服务提供商的恶意意图，通过编造产品/服务评论来操纵消费者。不道德的行为者使用 Sybil 帐户、机器人农场和购买真实帐户来宣传产品和诽谤竞争对手。面对垃圾评论技术的不断进步，研究界应该退后一步，评估迄今为止探索的打击虚假评论的方法，并重新组合以定义新的方法。本文回顾了在线平台上有关虚假评论检测 (FRD) 的文献。它涵盖了基础研究和商业解决方案，并讨论了当前方法和法规在防止欺骗性审查造成的损害方面取得有限成功的原因。