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http://dx.doi.org/10.5762/KAIS.2018.19.5.640

Analysis of Consumer Awareness of Cycling Wear Using Web Mining  

Kim, Chungjeong (Institute of Symbiotic Life-TECH, Yonsei University)
Yi, Eunjou (Department of Fashion & Textiles, Jeju National University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.19, no.5, 2018 , pp. 640-649 More about this Journal
Abstract
This study analyzed the consumer awareness of cycling wear using web mining, one of the big data analysis methods. For this, the texts of postings and comments related to cycling wear from 2006 to 2017 at Naver cafe, 'people who commute by bicycle' were collected and analyzed using R packages. A total of 15,321 documents were used for data analysis. The keywords of cycling wear were extracted using a Korean morphological analyzer (KoNLP) and converted to TDM (Term Document Matrix) and co-occurrence matrix to calculate the frequency of the keywords. The most frequent keyword in cycling wear was 'tights', including the opinion that they feel embarrassed because they are too tight. When they purchase cycling wear, they appeared to consider 'price', 'size', and 'brand'. Recently 'low price' and 'cost effectiveness' have become more frequent since 2016 than before, which indicates that consumers tend to prefer practical products. Moreover, the findings showed that it is necessary to improve not only the design and wearability, but also the material functionality, such as sweat-absorbance and quick drying, and the function of pad. These showed similar results to previous studies using a questionnaire. Therefore, it is expected to be used as an objective indicator that can be reflected in product development by real-time analysis of the opinions and requirements of consumers using web mining.
Keywords
Big Data; Consumer Awareness; Cycling Wear; Text Mining; Wearability; Web Mining;
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Times Cited By KSCI : 9  (Citation Analysis)
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