• 제목/요약/키워드: Overseas local newspaper

검색결과 2건 처리시간 0.015초

해외 현지신문의 한·중·일 문화콘텐츠 관련 기사의 내용분석 연구 -말레이시아, 싱가폴, 몽골, 우즈베키스탄, 스페인을 중심으로- (Content Analysis of the Articles of the Overseas Local Newspapers on the Culture Contents of Korea, China, and Japan -Focusing on Malaysia, Singapore, Mongolia, Uzbekistan, and Spain-)

  • 안춘순
    • 한국의류학회지
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    • 제40권6호
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    • pp.1100-1115
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    • 2016
  • This research investigated the relative influence of culture contents from Korea, China, and Japan published in the internet version of local newspapers for Malaysia, Mongolia, Uzbekistan, and Spain (from January 2010 to December 2014) and from Singapore (January 2012 to December 2014) using content analysis focused on the frequency distribution of newspaper content. 'Food' showed the highest appearance frequency of the 11 culture contents investigated in the study. Among the articles related to Korea, 'Pop Music' showed the highest frequency for Malaysia, Uzbekistan, and Spain and 'Star' showed the highest frequency for Singapore and Mongolia. Among the Hallyu related contents, 'Pop Music' showed the highest frequency followed by 'Star', 'Movie', and 'Drama'. Articles related to Korea showed a significantly higher frequency than articles related to China and Japan in 'Pop Music' and 'Star' categories. Spain showed articles related to Korea only in the 'Pop Music' category.

COVID-19 '덕분에 챌린지' 전후 간호사 관련 뉴스 기사의 토픽 모델링 및 키워드 네트워크 분석 (Topic Modeling and Keyword Network Analysis of News Articles Related to Nurses before and after "the Thanks to You Challenge" during the COVID-19 Pandemic)

  • 윤은경;김정옥;변혜민;이국근
    • 대한간호학회지
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    • 제51권4호
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    • pp.442-453
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    • 2021
  • 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.