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Research Trend Analysis in Fashion Design Studies in Korea using Topic Modeling

토픽모델링을 이용한 국내 패션디자인 연구동향 분석

  • Jang, Namkyung (Dept. of Textile and Fashion Design, Hansei University) ;
  • Kim, Min-Jeong (Dept. of Consumer Economics, Sookmyung Women's University)
  • 장남경 (한세대학교 섬유패션디자인학과) ;
  • 김민정 (숙명여자대학교 소비자경제학과)
  • Received : 2017.04.25
  • Accepted : 2017.06.20
  • Published : 2017.06.28

Abstract

This study explored research trends by investigating articles published in the Journal of Korean Society of Fashion Design from 2001 through 2015. English key words and abstracts were analyzed using text mining and topic modeling techniques. The findings are as followings. By the text mining technique, 183 core terms, appeared more than 30 times, were derived from 7137 words used in total 338 articles' key words and abstracts. 'Fashion' and 'design' showed the highest frequency rate. After that, the well-received topic modeling technique, LDA, was applied to the collected data sets. Several distinct sub-research domains strongly tied with the previous fashion design field, except for topics such as fashion brand marketing and digital technology, were extracted. It was observed that there are the growing and declining trends in the research topics. Based on findings, implication, limitation, and future research questions were presented.

Keywords

Fashion design;Research trends;Text mining;Topic modeling;Latent Dirichlet allocation

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