토픽모델링을 이용한 국내 패션디자인 연구동향 분석
Research Trend Analysis in Fashion Design Studies in Korea using Topic Modeling
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초록

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.

키워드

Fashion designResearch trendsText miningTopic modelingLatent Dirichlet allocation패션 디자인연구동향텍스트마이닝토픽모델링잠재 디리클레 할당
제목
토픽모델링을 이용한 국내 패션디자인 연구동향 분석
제목 (타언어)
Research Trend Analysis in Fashion Design Studies in Korea using Topic Modeling
저자
장남경김민정
DOI
10.14400/JDC.2017.15.6.415
발행일
2017-06
저널명
디지털융복합연구
15
6
페이지
415 ~ 423