%A Jiafen Wu,Feicheng Ma %T Detecting Product Review Spam: A Survey %0 Journal Article %D 2019 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2018.0959 %P 1-15 %V 3 %N 9 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4702.shtml} %8 2019-09-25 %X

[Objective] This paper reviews current studies on fighting product review spam. [Coverage] We searched “review spam” with eight major scholarly databases (e.g., WoS, CNKI and EI, etc.), and retrieved a total of 90 relevant papers. [Methods] First, we adopted systematic review procedure to identify and categorize the methods detecting product review spam. Then, we compared the impacts of spam features on detection performance. [Results] The spam features and detection methods were the key issues in fighting product review spam. The acquisition of large-scale annotation data was a challenging task for current research. [Limitations] We did not examine the detection and classification methods for spammers. [Conclusions] This paper analyzes spam detection methods from the perspectives of data acquisition, spamming features and detection methods. It offers suggestions and directions for future research.