J Korean Acad Nurs Adm.  2022 Sep;28(4):319-330. 10.11111/jkana.2022.28.4.319.

Analysis of Headline News about Nurses Before and After the COVID-19 Pandemic

• Baek SM
• Park M

• KMID: 2536042
• DOI: http://doi.org/10.11111/jkana.2022.28.4.319

Abstract

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.

Keyword

Nurses; News headline; COVID-19; Text mining; CONCOR analysis