Abstract:

E-commerce website's product reviews have a guiding effect on the user's purchase intention. However, spammers may create fake reviews to artificially promote or demote target products. Techniques for detecting review spam therefore have become an urgent need. We first divide the related researches into two categories: internal review (text features) -centric and external reviews (behavior features) -centric. Then, their research progresses on feature selection and machine learning methods are summarized. The common data sets in product review spam detection are summarized. Finally, we point out some potential research directions based on the review.

Key words: product review spam, text feature, behavior feature, opinion data set