Product Quality Assessment Based on Online Reviews

Chao Li, Jun Xiang and Shiqiang Chen
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Chao Li: Information Engineering College, Hubei University for Nationalities, Enshi, China
Jun Xiang: Information Engineering College, Hubei University for Nationalities, Enshi, China
Shiqiang Chen: Information Engineering College, Hubei University for Nationalities, Enshi, China

International Journal of Decision Support System Technology (IJDSST), 2019, vol. 11, issue 3, 81-97

Abstract: Reviews can reflect the degree of consumers' satisfaction and views on product quality, and consumers tend to read product reviews and then get helpful information about product quality before placing an order in e-commerce platforms. However, the existing research mainly focus on the assessment of review quality, fake review detection, opinion mining, and there is little research to assess product quality from the perspectives of product features based on reviews objectively and quantifialy. Therefore, the authors propose a method to assess product quality based on reviews in a granularity of product feature. The authors define the related quality dimensions and develop the corresponding assessment models, assess the review quality crawled from an e-commerce platform, then extract product features and opinion words from the quality reviews, and finally assess product quality on the extracted and consumer-concerned features. Experiment results demonstrate the methodology can achieve the assessment of product quality on any feature objectively and quantificationally.

Date: 2019
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