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
With the spread of Covid-19 worldwide in 2020, the future of the aviation industry is facing a tremendous crisis. This study aims to predict the change in Korean Air travel behavior after Covid-19. To this end, this study intends to measure the public"s perception and experience related to Travel bubble. Specifically, this study intends to analyze a huge amount of big data through analysis using text mining. To this end, the key word "Travel bubble" was searched on Naver, Daum, and Google from September 2020 to the May 2021. After deleting unnecessary words out of the total 5,334 words, text mining analysis was performed. This study extracted data and frequency through data collection and arranged words. With Textom, key word frequency analysis, TF-IDF analysis, N-gram analysis carried out. Using UCINET 6, this research analyzed the connection structure between key words and degree centrality and verified the degree of their relationships. Furthermore, this study conducted CONCOR analysis to draw a party formed by similar key words. This study is an appropriate research during post Covid-19. With Big data, this research found implications that could not be found in previous studies in the tourism field. Moreover, this study suggested a way to activate Travel bubble. As such, this study presented academic and practical implication for the aviation and tourism industry.
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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UCI(KEPA) : I410-ECN-0101-2022-323-001623803
