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Analysis of Media Articles on COVID-19 and Nurses Using Text Mining and Topic Modeling
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Ji Yeon An, Yun Jeong Yi, Bok Im Lee
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J Korean Acad Community Health Nurs. 2021;32(4):467-476. Published online December 31, 2021
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DOI: https://doi.org/10.12799/jkachn.2021.32.4.467
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- Purpose
The purpose of this study is to understand the social perceptions of nurses in the context of the COVID-19 outbreak through analysis of media articles.
Methods
Among the media articles reported from January 1st to September 30th, 2020, those containing the keywords ‘[corona or Wuhan pneumonia or covid] and [nurse or nursing]’ are extracted. After the selection process, the text mining and topic modeling are performed on 454 media articles using textom version 4.5.
Results
Frequency Top 30 keywords include ‘Nurse’, ‘Corona’, ‘Isolation’, ‘Support’, ‘Shortage’, ‘Protective Clothing’, and so on. Keywords that ranked high in Term Frequency-Inverse Document Frequency (TF-IDF) values are ‘Daegu’, ‘President’, ‘Gwangju’, ‘manpower’, and so on. As a result of the topic analysis, 10 topics are derived, such as ‘Local infection’, ‘Dispatch of personnel’, ‘Message for thanks’, and ‘Delivery of one’s heart’.
Conclusion
Nurses are both the contributors and victims of COVID-19 prevention. The government and the nurses’ community should make efforts to improve poor working conditions and manpower shortages.
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Citations
Citations to this article as recorded by  - The Need for and Perceptions of Interprofessional Education and Collaboration Among Undergraduate Students in Nursing and Medicine in South Korea
Hee-Young Song, Kyoung A Nam
Journal of Multidisciplinary Healthcare.2022; Volume 15: 847. CrossRef
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Health-risk Behaviors and Self-efficacy in Elderly Adolescents
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Ji Yeon An, Young Ran Tak
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J Korean Acad Community Health Nurs. 2006;17(3):387-396. Published online September 30, 2006
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Abstract
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- No abstract available.
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