Journal of the Korean Society of Clothing and Textiles (한국의류학회지)

The Korean Society of Clothing and Textiles (한국의류학회)
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Keywords Analysis of Clothing Materials in Consumer Reviews Using Big Data Text Mining

빅데이터 텍스트 마이닝을 활용한 소비자 리뷰에서의 의류 소재 키워드 분석

  • Gaeun Kang (Dept. of Clothing and Textiles, Kyung Hee University) ;
  • Jiwon Park (Dept. of Clothing and Textiles, Kyung Hee University) ;
  • Shinjung Yoo (Dept. of Clothing and Textiles, Kyung Hee University)
  • Received : 2024.03.04
  • Accepted : 2024.07.02
  • Published : 2024.08.31
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Abstract

This research explores consumer preferences for materials in different clothing product categories, using web-crawling and text mining techniques. Specifically, the study focuses on the material-related terms found in consumer reviews across three distinct product categories: functional clothing, formal shirts, and knit sweaters. Top-selling products within each category were identified on the Naver Shopping website based on the volume of reviews, and the four most-reviewed products were selected. Six hundred reviews per product were analyzed using the Textom big-data analysis software to determine the frequency of material-related mentions and word associations. The analysis utilized two comparative metrics: product category and usage duration. Our findings reveal notable variations in the material preferences mentioned by consumers across different product categories. The study suggests a need to re-evaluate existing standardized review criteria to better reflect consumer interests specific to each product category. Additionally, an increase in material-related terms in reviews over one month indicates the potential importance of extending the duration of product reviews to enhance the accuracy of information that reflects longer-term consumer experiences with material quality.

Keywords

Acknowledgement

이 논문은 2023년 교육부의 대학혁신지원사업 사업비 지원을 받아 수행된 연구임.

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