Abstract: With the rapid development of e-commerce,consumers have accepted online shopping increasingly,and the product reviews then have an great influence on consumers’ purchase decision.Product reviews refer to the evaluation or comment information of items or products written by online shopping users.These comments usually include some review spams that may hurt user shopping experiences.Review spam detection,therefore,becomes one of the important problems to improve service quality.In this paper,a review spam detection approach called LDA-SP(LDA-sentiment polarity) was proposed by carefully analyzing the main characteristic of review spams.First,we used LDA topic model to filter the irrelevant reviews,and then applied sentiment analysis to identify the untruthful reviews.Experiments were conducted on a large number of reviews data on a online shopping mall.Our experimental results show that the detection accuracy of LDA-SP method is higher than that of the traditional LDA topic model and the single sentiment polarity analysis method.It can effectively detect review spams,so that more objective and accurate information about products will be displayed to the users of e-commerce.

Key words: Product reviews,Review spam,Topic model,Sentiment analysis