A Novel Product Ranking Approach Considering Sentiment Intensity Distribution of Online Reviews - Sheng-qiang Gu; Shi-tong Liu; Yong Liu; Jia-ming Ding (International Journal of Computational Intelligence Systems)
Abstract Online reviews of products have a significant impact on consumers' purchasing decisions, making it important for both platform retailers and consumers to rank products, and eventually purchase products. With respect to the problem of product ranking that consists of the information contained in online reviews; by considering the sentiment intensity distribution of online reviews, we establish a fine-grained sentiment intensity analysis and then exploit grey incidence analysis and TOPSIS to establish a multi-attribute approach for product ranking. Finally, a case study of laptop purchases verifies the applicability and effectiveness of the proposed approach.