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Detecting Product Review Spam: A Survey |
Jiafen Wu,Feicheng Ma() |
Center for Studies of Information Resources, Wuhan University, Wuhan 430072, China |
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Abstract [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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Received: 31 August 2018
Published: 23 October 2019
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