Purpose
This study analyzed news titles related to nurses in Korea before and after the Coronavirus disease 2019 (COVID 19) pandemic, and aimed to identify the implications of media reports. Methods: Data from January 2019 to December 2020 were collected from BIGKINDS regarding Korean nurses. Text mining and CONCOR analysis were conducted on the top 30 keywords using TEXTOM and Ucinet 6. Results: From the findings of this study, keywords were related to Taewom and Newborn death in 2019. Additionally, because of COVID-19 and the controversy over the encouragement of President Moon Jae-in, Taewom was included in 2020. Using CONCOR analysis, 6 clusters (characteristics and results of major incidents, the issue related target, Newborn abuse, Taewom, drugs, nursing education) were generated in 2019, and 6 clusters (emergency room, hero, controversy, Taewom, COVID-19, hospital infection) were generated in 2020. Conclusion: Before and after the COVID-19 pandemic, most of the news headlines of nurses consisted of negative keywords, while there were few positive news headlines. In order to improve the image of nurses, it is necessary to continuously analyze media trends and establish strategies accordingly.

Citations

• Agendas on Nursing in South Korea Media: Natural Language Processing and Network Analysis of News From 2005 to 2022
  Daemin Park, Dasom Kim, Ah-hyun Park
  Journal of Medical Internet Research.2024; 26: e50518.     CrossRef
• Experiences of Caring for Cohort-Isolated Patients among Nurses in Locked Psychiatric Units
  Hyeran An, Kyungmi Kim, Jongeun Lee, Sunhwa Won
  Healthcare.2023; 11(19): 2650.     CrossRef