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.
초록·키워드
The purpose of this study is to investigate the status of Korean traditional costume content on YouTube, which is known as the mainstream Korean-wave. The intention of this study to analyze whether Korean traditional costume is using specific media strategies through YouTube as an effort to advance overseas. Also, it is meaningful to identify the current address of Korean traditional costume content on YouTube for the continuous development of the Korean-wave, and to contribute as a basic material for vitalization of Korean-wave based on traditional culture. The following is a research process to investigate the status of YouTube content related to Korean traditional costume. The first is to select keywords used Goggle Trends, which is a search statistics service provided by Google. Considering that YouTube is a global site, searched shall be done in both Korean and English words. Therefore, as the final keywords, “Hanbok” and ‘한복’ were selected. Second, analyzed contents of each keyword were divided into year, number of views, the contents of each keyword are divided into 5 categories – year, the number of views, subjects, details, and running-time - to be analyzed and to derive the results. As a result, the useage of YouTube content using Korean traditional costume as an item is gradually incresing in many ways, but still insufficient. Therefore, the types of content, message strategy, storytelling, creative strategies, and types of sources need to be diversify. In conclutsion, YouTube, which is the subject of this study, has a limitation that it is difficult to generalize only the current situation because of the rapid change due th the characteristics of the internet space. Therefore, continuous observation on the subject is required, and a specific contents strategy based on the traditional culture is needed as its follw-up research.
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.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2020-300-000231679
