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An Investigation of a Sensibility Evaluation Method Using Big Data in the Field of Design -Focusing on Hanbok Related Design Factors, Sensibility Responses, and Evaluation Terms-
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디자인 분야에서 빅데이터를 활용한 감성평가방법 모색 -한복 연관 디자인 요소, 감성적 반응, 평가어휘를 중심으로-

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Type
Academic journal
Author
An, Hyosun (이화여자대학교 의류학과) Lee, Inseong (이화여자대학교 의류산업학과)
Journal
The Korean Society of Clothing and Textiles 한국의류학회지 한국의류학회지 제40권 제6호 KCI Accredited Journals
Published
2016.1
Pages
1,034 - 1,044 (11page)

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An Investigation of a Sensibility Evaluation Method Using Big Data in the Field of Design -Focusing on Hanbok Related Design Factors, Sensibility Responses, and Evaluation Terms-
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This study seeks a method to objectively evaluate sensibility based on Big Data in the field of design. In order to do so, this study examined the sensibility responses on design factors for the public through a network analysis of texts displayed in social media. 'Hanbok', a formal clothing that represents Korea, was selected as the subject for the research methodology. We then collected 47,677 keywords related to Hanbok from 12,000 posts on Naver blogs from January $1^{st}$ to December $31^{st}$ 2015 and that analyzed using social matrix (a Big Data analysis software) rather than using previous survey methods. We also derived 56 key-words related to design elements and sensibility responses of Hanbok. Centrality analysis and CONCOR analysis were conducted using Ucinet6. The visualization of the network text analysis allowed the categorization of the main design factors of Hanbok with evaluation terms that mean positive, negative, and neutral sensibility responses. We also derived key evaluation factors for Hanbok as fitting, rationality, trend, and uniqueness. The evaluation terms extracted based on natural language processing technologies of atypical data have validity as a scale for evaluation and are expected to be suitable for utilization in an index for sensibility evaluation that supplements the limits of previous surveys and statistical analysis methods. The network text analysis method used in this study provides new guidelines for the use of Big Data involving sensibility evaluation methods in the field of design.

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