인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
학술저널
DBpia Top 10%
오류 신고하기해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
초록·키워드
This study explores academic research trends in the field of Korean beauty, commonly known as K-beauty, by employing advanced text-mining techniques. As global interest in K-beauty products and culture has rapidly increased, academic discourse surrounding K-beauty has likewise expanded. To systematically analyze this trend, 369 Korean academic papers containing the term “K-beauty” were collected from the Research Information Sharing Service database. These texts underwent a rigorous preprocessing procedure that included tokenization, part-of-speech tagging, and stopword removal, ensuring the quality and relevance of the extracted data. Keyword analysis was conducted using both CountVectorizer and Term Frequency–Inverse Document Frequency techniques. These complementary methods enabled the identification not only of frequently occurring keywords but also of contextually significant terms that might otherwise be overlooked. The extracted keywords were visualized using word clouds to highlight their relative prominence. To further uncover underlying patterns and relationships among terms, a keyword co-occurrence network was constructed and analyzed using four centrality measures—degree, closeness, betweenness, and eigenvector centrality—calculated via Python’s NetworkX library and visualized with UCINET software. The results revealed that keywords such as “cosmetics,” “brand,” and “industry” held dominant positions across all centrality measures, underscoring their foundational role in K-beauty research. Notably, “development” and “strategy” stood out in betweenness centrality, indicating their importance as conceptual bridges connecting different thematic clusters. Eigenvector centrality further highlighted clusters of highly influential terms, suggesting the presence of core themes shaping academic discourse. The findings point to a robust and interconnected research network characterized by both structural cohesion and thematic diversity. Unlike prior studies that focused on specific cases or limited timeframes, this study provides a holistic, data-driven overview of the evolving academic landscape in K-beauty. The results offer valuable insights for scholars, practitioners, and policymakers interested in strategic research planning, topic identification, and cross-disciplinary collaboration within the field of beauty studies.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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