Astroturfing is a phenomenon in which sponsors of fake messages or reviews are masked because their intentions are not genuine. Astroturfing reviews are intentionally made to influence people to take decisions in favour of or against a target service or product or organization. The tourism sector being one of the sectors that is flourishing and witnessing unprecedented growth is affected by the activities of astroturfers. Astroturfing reviews can cause many problems to tourists who make decisions based on available online reviews. However, authentic and genuine reviews help people make informed decisions. In this paper a Latent Dirichlet Allocation (LDA) based Group Topic-Author model is proposed for efficient discovery of social astroturfing groups within the tourism domain. An algorithm named Astroturfing Group Topic Detection (AGTD) is defined for the implementation of the proposed model. The experimental results of this study revealed the utility of the proposed system for the discovery of social astroturfing groups within the tourism domain.

中文翻译：

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有效发现旅游领域潜在社会群体的群组主题-作者模型

Astroturfing 是一种现象，在这种现象中，虚假信息或评论的赞助商被掩盖，因为他们的意图不真实。Astroturfing 评论是有意影响人们做出支持或反对目标服务、产品或组织的决定。旅游业是蓬勃发展并见证空前增长的行业之一，受到了astroturfers活动的影响。Astroturfing 评论可能会给根据可用在线评论做出决定的游客带来许多问题。然而，真实和真实的评论有助于人们做出明智的决定。在本文中，提出了一种基于潜在狄利克雷分配 (LDA) 的组主题-作者模型，以有效地发现旅游领域内的社会 astroturfing 组。为实现所提出的模型定义了一种名为 Astroturfing Group Topic Detection (AGTD) 的算法。这项研究的实验结果揭示了所提出的系统在旅游领域内发现社会 astroturfing 群体的效用。