Analyzing and Detecting Adversarial Spam on a Large-scale Online APP Review System
Jianyu Wang, Rui Xia Wen, Chunming Wu, Jian Xiong · Companion Proceedings of the Web Conference 2020 · 2020
The online review system provides a platform for consumers to express their opinions and make decisions. However, the spam review has become a widespread problem recently. Existing detection systems are mostly designed for fraudsters who write fake reviews to promote their products or mislead consumers in E-commerce (e.g., Amazon, Yelp, Alibaba). In this paper, we focus on spams in the large-scale online app review platform. Through an in-depth analysis of 5 million reviews from the Tencent App store, we find almost half of the reviews are spams. Even worse, most of the reviews are deliberately designed by fraud reviewers for misleading classifiers. Specially, we conclude three popular patterns of generating adversarial spams by attackers.