텍스트 마이닝(text mining) 기법을 활용한 서브버시브 베이식(subversive basics) 패션의 특성
Evaluating the Characteristics of Subversive Basic Fashion Utilizing Text Mining Techniques
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Fashion trends are actively disseminated through social media, which influences both their propagation and consumption. This study explored how users perceive subversive basic fashion in social media videos, by examining the associated concepts and characteristics. In addition, the factors contributing to the style's social media dissemination were identified and its distinctive features were analyzed. Through text mining analysis, 80 keywords were selected for semantic network and CONCOR analysis. TF-IDF and N-gram results indicate that subversive basic fashion involves transformative design techniques such as cutting or layering garments, emphasizing the body with thin fabrics, and creating bold visual effects. Topic modeling suggests that this fashion forms a subculture that resists mainstream norms, seeking individuality by creatively transforming the existing garments. CONCOR analysis categorized the style into six groups: forward-thinking unconventional fashion, bold and unique style, creative reworking, item utilization and combination, pursuit of easy and convenient fashion, and contemporary sensibility. Consumer actions, linked to social media, were shown to involve easily transforming and pursuing personalized styles. Furthermore, creating new styles through the existing clothing is seen as an economic and creative activity that fosters network formation and interaction. This study is significant as it addresses language expression limitations and subjectivity issues in fashion image analysis, revealing factors contributing to content reproduction through user-perceived design concepts and social media-conveyed fashion characteristics.
Abstract
Fashion trends are actively disseminated through social media, which influences both their propagation and consumption. This study explored how users perceive subversive basic fashion in social media videos, by examining the associated concepts and characteristics. In addition, the factors contributing to the style's social media dissemination were identified and its distinctive features were analyzed. Through text mining analysis, 80 keywords were selected for semantic network and CONCOR analysis. TF-IDF and N-gram results indicate that subversive basic fashion involves transformative design techniques such as cutting or layering garments, emphasizing the body with thin fabrics, and creating bold visual effects. Topic modeling suggests that this fashion forms a subculture that resists mainstream norms, seeking individuality by creatively transforming the existing garments. CONCOR analysis categorized the style into six groups: forward-thinking unconventional fashion, bold and unique style, creative reworking, item utilization and combination, pursuit of easy and convenient fashion, and contemporary sensibility. Consumer actions, linked to social media, were shown to involve easily transforming and pursuing personalized styles. Furthermore, creating new styles through the existing clothing is seen as an economic and creative activity that fosters network formation and interaction. This study is significant as it addresses language expression limitations and subjectivity issues in fashion image analysis, revealing factors contributing to content reproduction through user-perceived design concepts and social media-conveyed fashion characteristics.
참고문헌 (31)
- Blei, D. M., "Latent dirichlet allocation", Journal of Machine Learning Research, 3, pp.993~1022 (2003)
- 조한아, "인터넷 밈으로 가치가 있는 패션디자인 특성 연구", 한국패션디자인학회지, 20(2), pp.87~102 (2020), 한국패션디자인학회[DOI]
- 정수진, "소셜 미디어에 나타난 패션 액티비즘 - 이상미 해체 현상을 중심으로 -", 한국패션디자인학회지, 20(2), pp.55~72 (2020), 한국패션디자인학회[DOI]
- Interactivity and revisits to websites: A theoretical framework, "Dholakia, R. R", RITIM, ~ (2000)
- Heeter, C., "Media use in the information age: Emerging patterns of adoption and consumer use", pp.217~235 (1989), Lawrence Erlbaum Associates
- "Subversive basics: Flaunt wardrobe staples with a rebellious twist" (2022)[URL]
- 김건아, "빅 데이터를 이용한 제품디자인의 감성반응 분석 - 스마트폰을 대상으로 -", 한국과학예술융합학회, 27, pp.31~48 (2017), 한국전시산업융합연구원[DOI]
- 김지형, "빅데이터 텍스트 마이닝 분석을 활용한 아메카지 패션 트렌드 특징 고찰", 패션 비즈니스, 26(3), pp.138~154 (2022), 한국패션비즈니스학회
- 김학선, "빅데이터를 활용한 음식관광관련 의미연결망 분석의 탐색적 적용", Culinary Science & Hospitality Research, 23(4), pp.22~32 (2017), (사)한국조리학회[DOI]
- 김진희, "언어네트워크분석을 통해 본 과학중점학교 과학수업의 특징", 한국과학교육학회지, 38(4), pp.565~574 (2018), 한국과학교육학회[DOI]
- Kim, Y., "소셜네트워크분석 기법의 이해와 적용: 네트워크 구조와 클러스터링 그리고 QAP", Korea Institute of Public Administration, 34, pp.58~68 (2020)
- Kim, Y. H., "사회연결망 분석" (2016), Pakyoungsa
- 이진, "숏폼 동영상 콘텐츠의 유형 연구", 인문콘텐츠, (58), pp.121~139 (2020), 인문콘텐츠학회
- 이정학, "소셜 네트워크 빅데이터 분석을 활용한 2018 평창올림픽 키워드 분석", 한국스포츠산업경영학회지, 22(6), pp.73~89 (2017), 한국스포츠산업경영학회[DOI]
- 이진, "재가공형 숏폼 콘텐츠의 특성 연구", 한국콘텐츠학회 논문지, 22(5), pp.67~80 (2022), 한국콘텐츠학회[DOI]
- Lee, S., "네트워크 분석 방법론" (2012), Nonhyeong
- "The subversive basics trend is about rebellion" (2022)[URL]
- 이성직, "TF‐IDF의 변형을 이용한 전자뉴스에서의 키워드 추출 기법", 한국전자거래학회지, 14(4), pp.59~73 (2009), 한국전자거래학회
- "‘짧고, 강한’ 콘텐츠가 통한다" (2021)[URL]
- 남춘호, "일기자료 연구에서 토픽모델링 기법의 활용가능성 검토", 비교문화연구, 22(1), pp.89~135 (2016), 비교문화연구소
- "Orange"[URL]
- 박치성, "텍스트 네트워크 분석: 사회적 인식 네트워크(socio-cognitive network) 분석을 통한 정책이해관계자 간 공유된 의미 파악 사례", 정부학연구, 19(2), pp.73~108 (2013), 정부학연구소
- 박준형, "국내 기록관리학 연구동향 분석을 위한 토픽모델링 기법 비교 - LDA와 HDP를 중심으로 -", 한국도서관·정보학회지, 48(4), pp.235~258 (2017), 한국도서관·정보학회[DOI]
- "How subversive basics became TikTok’s favorite fashion hack" (2022)[URL]
- Rafaeli, S., "Interactivity from new media to communication", Advancing Communication Science: Merging Mass and Interpersonal Processes, pp.110~134 (1988), Sage
- 심혜령, "SNS에서 제공되는 시각적 정보의 사회적 거리가 패션 스타일 선호에 미치는 영향", 한국의류학회지, 42(2), pp.327~341 (2018), 한국의류학회
- "Subversion"[URL]
- "Text mining"[URL]
- Wasserman, S., "Social network analysis: Methods and applications" (1994), Cambridge University Press
- 양회창, "LDA를 이용한 HMR 연구동향 토픽모델링 분석", 물류학회지, 32(1), pp.81~92 (2022), 한국물류학회
- 장수방, "소셜미디어 빅데이터 분석을 활용한 복고미래주의 패션 이미지 분석", 한국디자인리서치, 7(3), pp.213~223 (2022), 한국디자인리서치학회[DOI]