[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.
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