텍스트 마이닝을 활용한 윤리적 패션 연구동향: 2009-2019 연구 네트워크 분석open accessEthical Fashion Research Trend Using Text Mining:Network Analysis of the Published Literature 2009-2019
- Other Titles
- Ethical Fashion Research Trend Using Text Mining:Network Analysis of the Published Literature 2009-2019
- Authors
- 최영현; 이규혜
- Issue Date
- Apr-2020
- Publisher
- 한국의류산업학회
- Keywords
- ethical fashion (윤리적 패션); sustainable fashion (지속가능한 패션); text mining (텍스트 마이닝); network analysis (네트워크 분석)
- Citation
- 한국의류산업학회지, v.22, no.2, pp.181 - 191
- Indexed
- KCI
- Journal Title
- 한국의류산업학회지
- Volume
- 22
- Number
- 2
- Start Page
- 181
- End Page
- 191
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/145841
- DOI
- 10.5805/SFTI.2020.22.2.181
- ISSN
- 1229-2060
- Abstract
- The fashion industry has faced environmental, social, and ethical issues due to increased interest in ethical consumption. Numerous ethical studies have been conducted in the fashion industry. This study looked at the current state of research by year, academic journal, and detail in major related papers published in Scopus, KCI and KCI between 2009 and 2019. Ethical fashion studies began to appear in 2009 and were concentrated in certain academic journals and focused on fashion marketing and fashion design. Topics in ethical fashion were terms such as sustainable, eco-friendly, up-cycling, recycling, eco, zero-waist, and organic. In ethical fashion studies, environmental studies were conducted most often; in addition, the terms used along with ethical fashion tend to be frequently used for each particular major. Looking at key words used in research by period, the study showed that research was most diverse between 2016 and 2019. In particular, environmental and social issues of ethical fashion and convergence with animal protection, new distribution, science and technology sectors were newly added between 2016 and 2019. This study used text mining and network analysis to understand the overall trends of ethical fashion studies in Korea. In conclusion it is important to realize the relationship between the main words along with the current status analysis.
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