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Article

Online User Review Analysis for Product Evaluation and Improvement

1
College of Creativity and Art Design, Zhejiang University City College, Hangzhou 310015, China
2
College of Computer Science and Technology, Zhejiang University, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
Academic Editor: Eduardo Álvarez-Miranda
J. Theor. Appl. Electron. Commer. Res. 2021, 16(5), 1598-1611; https://doi.org/10.3390/jtaer16050090
Received: 11 April 2021 / Revised: 8 May 2021 / Accepted: 11 May 2021 / Published: 13 May 2021
(This article belongs to the Section e-Commerce Analytics)
Traditional user research methods are challenged for the decision-making in product design and improvement with the updating speed becoming faster, considering limited survey scopes, insufficient samples, and time-consuming processes. This paper proposes a novel approach to acquire useful online reviews from E-commerce platforms, build a product evaluation indicator system, and put forward improvement strategies for the product with opinion mining and sentiment analysis with online reviews. The effectiveness of the method is validated by a large number of user reviews for smartphones wherein, with the evaluation indicator system, we can accurately predict the bad review rate for the product with only 9.9% error. And improvement strategies are proposed after processing the whole approach in the case study. The approach can be applied for product evaluation and improvement, especially for the products with needs for iterative design and sailed online with plenty of user reviews. View Full-Text
Keywords: online review; opinion mining; product evaluation; improvement strategy; product design; sentiment analysis online review; opinion mining; product evaluation; improvement strategy; product design; sentiment analysis
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MDPI and ACS Style

Yang, C.; Wu, L.; Tan, K.; Yu, C.; Zhou, Y.; Tao, Y.; Song, Y. Online User Review Analysis for Product Evaluation and Improvement. J. Theor. Appl. Electron. Commer. Res. 2021, 16, 1598-1611. https://doi.org/10.3390/jtaer16050090

AMA Style

Yang C, Wu L, Tan K, Yu C, Zhou Y, Tao Y, Song Y. Online User Review Analysis for Product Evaluation and Improvement. Journal of Theoretical and Applied Electronic Commerce Research. 2021; 16(5):1598-1611. https://doi.org/10.3390/jtaer16050090

Chicago/Turabian Style

Yang, Cheng, Lingang Wu, Kun Tan, Chunyang Yu, Yuliang Zhou, Ye Tao, and Yu Song. 2021. "Online User Review Analysis for Product Evaluation and Improvement" Journal of Theoretical and Applied Electronic Commerce Research 16, no. 5: 1598-1611. https://doi.org/10.3390/jtaer16050090

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