국내 간호사 관련 동영상 키워드의 네트워크 분석:유튜브 동영상 제목을 중심으로
Network Analysis of Keywords Related to Korean Nurse:Focusing on YouTube Video Titles
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Purpose: To analyze Korean nurse-related channels and video titles on YouTube, the world's largest online video sharing and social media platform, to clarify public opinion and image of nurses. We seek utilization strategies and measures through current status analysis. Methods: Data is collected by crawling video information related to Korean nurses, and correlation is analyzed with frequent word analysis and keyword network analysis. Results: Through the YouTube algorithm, 2,273 videos of ‘Nurse’ were analyzed in order of recent views, relevance, and rating, and 2,912 videos searched for with the keyword ‘Nurse + Hospital, COVID-19, Awareness, University, National Examination’ were analyzed. Numerous videos were uploaded, and nursing work that was uploaded in the form of a vlog recorded a high number of views. Conclusion: We could see if the YouTube video shows images of nurses. It has been confirmed that various information is being exchanged rather than information just for promotional purposes.
Abstract
Purpose: To analyze Korean nurse-related channels and video titles on YouTube, the world's largest online video sharing and social media platform, to clarify public opinion and image of nurses. We seek utilization strategies and measures through current status analysis. Methods: Data is collected by crawling video information related to Korean nurses, and correlation is analyzed with frequent word analysis and keyword network analysis. Results: Through the YouTube algorithm, 2,273 videos of ‘Nurse’ were analyzed in order of recent views, relevance, and rating, and 2,912 videos searched for with the keyword ‘Nurse + Hospital, COVID-19, Awareness, University, National Examination’ were analyzed. Numerous videos were uploaded, and nursing work that was uploaded in the form of a vlog recorded a high number of views. Conclusion: We could see if the YouTube video shows images of nurses. It has been confirmed that various information is being exchanged rather than information just for promotional purposes.
참고문헌 (30)
- Burgess J, "YouTube: Online video and participatory culture" (2016), Polity Press
- 한석희, "국내에서 제작된 인기 YouTube 채널 분석", 한국인터넷방송통신학회 논문지, 18(2), pp.11~17 (2018), 한국인터넷방송통신학회[DOI]
- 2020 Broadcast media usage behavior patterns, "Jung YC", Korea Communication Commission, ~, pp.11-B55212600003910 (2020)
- 이상숙, "유튜브 이용 동기에 대한 세대 간 상호인식 차이: 중장년층과 청년층 간 비교", 한국방송학보, 34(2), pp.76~104 (2020), 한국방송학회[DOI]
- Kim TY, "A study on the social and psychological predictors of the YouTube use motivation", Master, pp.2019
- Nancy R. Ahern, "Risky Behaviors and Social Networking Sites: How Is YouTube Influencing Our Youth?", Journal of Psychosocial Nursing and Mental Health Services, 53(10), pp.25~29 (2015), SLACK, Inc.[DOI]
- "Severance YouTube channel" (2010)[URL]
- "Moving from an importer of advanced medicine to an exporter" (2009)[URL]
- "Korean nurses association YouTube channel" (2018)[URL]
- "Guseul, the next door nurse" (2019)[URL]
- "Ganogano nurse daily" (2013)[URL]
- Skiba DJ, "Nursing education 2.0: YouTube™", Nursing Education Perspectives, 28(2), pp.100~102 (2007)
- Janice Agazio, "An untapped resource: Using YouTube in nursing education", Nurse Educator, 34(1), pp.23~28 (2009), Ovid Technologies (Wolters Kluwer Health)[DOI]
- Eileen Beal, "Nursing's Image on YouTube", AJN, American Journal of Nursing, 112(10), pp.17~ (2012), Ovid Technologies (Wolters Kluwer Health)[DOI]
- Jacinta Kelly, "The image of you: constructing nursing identities in YouTube", Journal of Advanced Nursing, 68(8), pp.1804~1813 (2011), Wiley[DOI]
- 박선아, "인터넷 신문에 나타난 간호사 이미지", 문화와융합, 39(6), pp.677~700 (2017), 한국문화융합학회[DOI]
- 윤영미, "토픽 모델링을 활용한 COVID-19 발생 전후 간호사 관련 토픽 비교: 인터넷 포털과 소셜미디어를 중심으로", 근관절건강학회지, 27(3), pp.255~267 (2020), 대한근관절건강학회[DOI]
- 윤은경, "COVID-19 ‘덕분에 챌린지’ 전후 간호사 관련 뉴스 기사의 토픽 모델링 및 키워드 네트워크 분석", Journal of Korean Academy of Nursing, 51(4), pp.442~453 (2021), 한국간호과학회
- Reed FL, "Beyond god's work: A thematic analysis of nurse image during the COVID-19 pandemic", pp.2021
- 신미선, "일반인이 지각하는 간호사 이미지 -주관적 이미지와 대중매체적 이미지-", Journal of The Korean Data Analysis Society, 14(2), pp.937~948 (2012), 한국자료분석학회[DOI]
- 박민영, "COVID-19 발생 전·후 언론보도에 나타난 간호사 이미지에 대한 텍스트 네트워크 분석 및 토픽 모델링", Journal of Korean Academy of Nursing, 52(3), pp.291~307 (2022), 한국간호과학회
- 이현숙, "인터넷과 소셜미디어를 통해 본 간호사 이미지에 관한 연구", 임상간호연구, 22(2), pp.173~182 (2016), 병원간호사회
- 이종화, "Python을 이용한 SNS 크롤링 시스템 구축", 한국산업정보학회논문지, 23(5), pp.61~76 (2018), 한국산업정보학회[DOI]
- Kalra GS, "YouTube video classification based on title and description text", 2019International Conference on Computing, Communication, and Intelligent Systems, pp.74~79 (2019), IEEE
- Kready J, "YouTube data collection using parallel processing", 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp.1119~1122 (2020)
- "YouTube Data API"[URL]
- "KoNLP(Korean NLP package)" (2016)[URL]
- 윤지영, "유튜브 브이로그 이용 동기 및 이용자 특성이 이용 만족 및 지속이용의도에 미치는 영향", 한국콘텐츠학회 논문지, 20(4), pp.189~201 (2020), 한국콘텐츠학회[DOI]
- Csárdi, G., "Statistical network analysis with igraph", pp.97~148 (2016), Springer
- 백수미, "COVID-19 팬데믹 전후 국내 언론 헤드라인의 간호사 이슈 분석", 간호행정학회지, 28(4), pp.319~330 (2022), 간호행정학회