빅데이터 텍스트 마이닝을 활용한 소비자 리뷰에서의 의류 소재 키워드 분석 = Keywords Analysis of Clothing Materials in Consumer Reviews Using Big Data Text Mining

다국어 초록 (Multilingual 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.