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언어 네트워크 분석을 통한 화장행동 연구동향 분석

Language network analysis of make-up behavior research

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참고문헌

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주제분류생활과학

초록

Research on cosmetic behavior has developed significantly since the 2000s. Reviewing cosmetic behavior research can be meaningful because it can grasp trends in the domestic cosmetics market, and it can also illuminate how domestic consumers’ interest in makeup has changed over time. The purpose of this study is to investigate the links between major keywords and the keywords which affect makeup behavior of different age groups through network analysis. In this study we analyzed thesis and journal data based on makeup behavior through network analysis using Nodexl. We analyzed 10 years of journals and theses - from 2000 to 2017, and investigated age-related differences in variables related to makeup behavior. Research subjects were divided into age-based groups: 10, 20-40, and over 50. The total number of theses collected was 82. In order to perform network analysis using the Nodexl program, we extracted the frequency of representative words using the KrKwic program. The extracted core words were analyzed for degree centrality, betweenness centrality and eigenvector centrality using Nodexl. The expected result is that the network analysis using keywords will lead to different variables depending on age and the main goal of the cosmetics market, and it is expected to be used as the basis for follow-up research related to cosmetic behavior.

Abstract

Research on cosmetic behavior has developed significantly since the 2000s. Reviewing cosmetic behavior research can be meaningful because it can grasp trends in the domestic cosmetics market, and it can also illuminate how domestic consumers’ interest in makeup has changed over time. The purpose of this study is to investigate the links between major keywords and the keywords which affect makeup behavior of different age groups through network analysis. In this study we analyzed thesis and journal data based on makeup behavior through network analysis using Nodexl. We analyzed 10 years of journals and theses - from 2000 to 2017, and investigated age-related differences in variables related to makeup behavior. Research subjects were divided into age-based groups: 10, 20-40, and over 50. The total number of theses collected was 82. In order to perform network analysis using the Nodexl program, we extracted the frequency of representative words using the KrKwic program. The extracted core words were analyzed for degree centrality, betweenness centrality and eigenvector centrality using Nodexl. The expected result is that the network analysis using keywords will lead to different variables depending on age and the main goal of the cosmetics market, and it is expected to be used as the basis for follow-up research related to cosmetic behavior.

참고문헌 (12)

  1. 안성남, "NCS 도입에 따른 뷰티서비스 분야의 연구 동향 분석", 한국디자인문화학회지, 23(4), pp.551~558 (2017), 한국디자인문화학회
  2. 최지혜, "뷰티 태도 관련 기존 연구의 분석", 복식문화연구, 24(6), pp.756~776 (2016), 복식문화학회[DOI]
  3. Kim, H. H., "A study of the make-up behaviors and consumers anxiety in purchasing cosmetics of the female high school student", Journal of the Korean Society of Clothing and Textiles, 26(2), pp.251~262 (2002)
  4. 김정숙, "여대생의 화장행동 및 화장 전·후 자아개념에 관한 연구", 한국의류산업학회지, 7(6), pp.633~640 (2005), 한국의류산업학회
  5. Kim, K. -M., "Analysis on research trends of papers published in the Korean Society of Beauty Industry Journal", Journal of Beauty Industry, 10(2), pp.15~32 (2016)
  6. Kwon, J. -H., "Bibliometric analysis on the research trends in field hair style", Journal of Beauty Industry, 9(2), pp.23~36 (2015)
  7. 이헤원, "미용서비스 개념 체계와 미용서비스 만족에 관한 기존 연구 분석", 한국미용학회지, 20(1), pp.127~137 (2014), 한국미용학회
  8. 이재윤, "계량서지적 네트워크 분석을 위한 중심성 척도에 관한 연구", 한국문헌정보학회지, 40(3), pp.191~214 (2006), 한국문헌정보학회
  9. Lee, S. -S., (2012), Nonhyeong
  10. 이수상, "언어 네트워크 분석 방법을 활용한 학술논문의 내용분석", 정보관리학회지, 31(4), pp.49~68 (2014), 한국정보관리학회[DOI]
  11. NodeXL Korea., (2015), Paradigmbook
  12. Park, B. -N., "A bibliometrics analysis on research trends in the field of beauty management", Journal of Beauty Industry, 12(1), pp.87~102 (2018)

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