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KMID : 0123520200270030255
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Journal of muscle and joint health
2020 Volume.27 No. 3 p.255 ~ p.267
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Comparison of Topics Related to Nurse on the Internet Portals and Social Media Before and During the COVID-19 era Using Topic Modeling
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Yoon Young-Mi
Kim Seong-Kwang
Kim Hye-Kyeong
Kim Eun-Joo
Jeong Yun-Eui
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Abstract
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Purpose: The purpose of this study is to compare topics through keywords related to nurses in internet portals and social media Pre coronavirus disease (COVID-19) era and during the COVID-19 era.
Methods: For six months before and during the outbreak of COVID-19 in Korea, "nurse" was searched on the internet. For data collection, we implemented web crawlers in programming languages such as Python and collected keywords. The keywords collected were classified into three domains of topic Modeling.
Results: The keyword 'nurse' increased by 15% during COVID-19 era. Keywords that ranked high in Term Frequency - Inverse Document Frequency (TF-IDF) values were before COVID-19, such as "nurse" and "C-section". during COVID-19, however, they were not only "nurse" but also "emergency" and "gown" related to pandemics.
Conclusion: Various topics were being uploaded into the internet media. Nursing professionals should be interested in the text that is revealed in the internet media and try to continuously identify and improve problems.
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KEYWORD
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Nurse, COVID-19, Social media
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