COVID-19 ‘덕분에 챌린지’ 전후 간호사 관련 뉴스 기사의 토픽 모델링 및 키워드 네트워크 분석.

Purpose: This study was conducted to assess public awareness and policy challenges faced by practicing nurses. Methods: After collecting nurse-related news articles published before and after 'the Thanks to You Challenge' campaign (between December 31, 2019, and July 15, 2020), keywords were extract...

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Publicado en:Journal of Korean Academy of Nursing Vol. 51; no. 4; pp. 442 - 454
Autores principales: 윤은경, 김정옥, 변혜민, 이국근
Formato: research tables/charts Journal Article
Publicado: Korean Society of Nursing Science Aug2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2021
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        atl: COVID-19 ‘덕분에 챌린지’ 전후 간호사 관련 뉴스 기사의 토픽 모델링 및 키워드 네트워크 분석.
      aug:
        au:
          윤은경
          김정옥
          변혜민
          이국근
        affil: 경희대학교 간호과학대학
      sug:
        subj:
          COVID-19 Pandemic
          Social Network Analysis
          Newsletters
          Health Policy
          Nurse Attitudes
          Human
          COVID-19 Transmission
          South Korea
          Nurses
          Advanced Practice Registered Nurses
          Attitude to Illness
      ab: Purpose: This study was conducted to assess public awareness and policy challenges faced by practicing nurses. Methods: After collecting nurse-related news articles published before and after 'the Thanks to You Challenge' campaign (between December 31, 2019, and July 15, 2020), keywords were extracted via preprocessing. A three-step method keyword analysis, latent Dirichlet allocation topic modeling, and keyword network analysis was used to examine the text and the structure of the selected news articles. Results: Top 30 keywords with similar occurrences were collected before and after the campaign. The five dominant topics before the campaign were: pandemic, infection of medical staff, local transmission, medical resources, and return of overseas Koreans. After the campaign, the topics 'infection of medical staff' and 'return of overseas Koreans' disappeared, but 'the Thanks to You Challenge' emerged as a dominant topic. A keyword network analysis revealed that the word of nurse was linked with keywords like thanks and campaign, through the word of sacrifice. These words formed interrelated domains of 'the Thanks to You Challenge' topic. Conclusion: The findings of this study can provide useful information for understanding various issues and social perspectives on COVID-19 nursing. The major themes of news reports lagged behind the real problems faced by nurses in COVID-19 crisis. While the press tends to focus on heroism and whole society, issues and policies mutually beneficial to public and nursing need to be further explored and enhanced by nurses.
      pubtype: Academic Journal
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      ougenre: Article
    language: Korean
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