王冠宁Wang Guanning

澳門城市大學設計學博士

How to extract design knowledge from online reviews: extracting and evaluating typical product characteristics by using web-based text mining


Journal article


Guanning Wang
Conference on Electronic Information Engineering and Data Processing, 2025

Semantic Scholar DOI
Cite

Cite

APA   Click to copy
Wang, G. (2025). How to extract design knowledge from online reviews: extracting and evaluating typical product characteristics by using web-based text mining. Conference on Electronic Information Engineering and Data Processing.


Chicago/Turabian   Click to copy
Wang, Guanning. “How to Extract Design Knowledge from Online Reviews: Extracting and Evaluating Typical Product Characteristics by Using Web-Based Text Mining.” Conference on Electronic Information Engineering and Data Processing (2025).


MLA   Click to copy
Wang, Guanning. “How to Extract Design Knowledge from Online Reviews: Extracting and Evaluating Typical Product Characteristics by Using Web-Based Text Mining.” Conference on Electronic Information Engineering and Data Processing, 2025.


BibTeX   Click to copy

@article{guanning2025a,
  title = {How to extract design knowledge from online reviews: extracting and evaluating typical product characteristics by using web-based text mining},
  year = {2025},
  journal = {Conference on Electronic Information Engineering and Data Processing},
  author = {Wang, Guanning}
}

Abstract

Product reviews provided by shopping websites can be analysed by designers, as each customer review condenses the user's unique experience and emotions about the product. It is important to capture the content of user reviews as early as possible in the product development process. Utilizing user reviews as data offers designers comprehensive, cost-effective, and rapid evaluations, while also inspiring new ideas for iteration. Although product reviews are valuable to designers, analyzing tens of thousands of reviews using conventional methods is time-consuming and labor-intensive. This study aims to propose a method for rapidly analyzing review data using the LDA model to enhance designers' creativity. This method was applied to a popular coffee maker from a leading Chinese shopping website (www.JD.com), where we conducted textual analysis of purchased user reviews and examined product features alongside review themes. This paper describes an effective methodology for generating design ideas from user reviews, which allows designers to utilise this information and gain insight into the issues involved in the product creation process.