A Method for Ranking Products Through Online Reviews Based on Sentiment Classification and Interval-Valued Intuitionistic Fuzzy TOPSIS

Yang Liu (), Jian-Wu Bi and Zhi-Ping Fan
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Yang Liu: Department of Information Management and Decision Sciences, School of Business Administration, Northeastern University, Shenyang 110167, P. R. China
Jian-Wu Bi: Department of Information Management and Decision Sciences, School of Business Administration, Northeastern University, Shenyang 110167, P. R. China
Zhi-Ping Fan: Department of Information Management and Decision Sciences, School of Business Administration, Northeastern University, Shenyang 110167, P. R. China†State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, P. R. China

International Journal of Information Technology & Decision Making (IJITDM), 2017, vol. 16, issue 06, 1497-1522

Abstract: Studies have shown that online product reviews significantly affect consumer purchase decisions. However, it is difficult for the consumer to read online product reviews one by one because the number of online reviews is very large. Thus, to facilitate consumer purchase decisions, how to rank products through online reviews is a valuable research topic. This paper proposes a method for ranking products through online reviews based on sentiment classification and the interval-valued intuitionistic fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The method consists of two parts: (1) identifying sentiment orientations of the online reviews based on sentiment classification and (2) ranking alternative products based on interval-valued intuitionistic fuzzy TOPSIS. In the first part, the online reviews of the alternative products concerning multiple attributes are preprocessed, and an algorithm based on support vector machine and one-versus-one strategy is developed for classifying the sentiment orientations of online reviews into three categories: positive, neutral, and negative. In the second part, based on the percentages of the online reviews with different sentiment orientations and the numbers of online reviews of different products crawled from the website, an interval-valued intuitionistic fuzzy number is constructed to represent the performance of an alternative product with respect to the product attribute. Additionally, the interval-valued intuitionistic fuzzy TOPSIS method is employed to determine a ranking of the alternative products. Finally, a case analysis is provided to illustrate the application of the proposed method.

Keywords: Product ranking; online reviews; SVM; sentiment classification; interval-valued intuitionistic fuzzy number; TOPSIS (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (8)

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DOI: 10.1142/S021962201750033X

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