|
|
|
|
박민영 ( Park Min-Young ) - Jeonbuk National University Hospital Department of Nursing
정석희 ( Jeong Seok-Hee ) - Chonbuk National University College of Nursing
김희선 ( Kim Hee-Sun ) - Chonbuk National University College of Nursing
이은지 ( Lee Eun-Jee ) - Chonbuk National University College of Nursing
|
|
Abstract
|
|
|
|
|
Purpose: To identify the main keywords, the network structure, and the main topics of press articles related to nurses appeared in media reports.
Methods: Data were media articles related to ‘nurse’ reported in a total of 16 central media for one year (Before COVID-19: July 1 - December 31, 2019; After COVID-19, January 1 - June 30, 2020). Data were collected in ‘Big Kinds’ database. A total of 7,800 articles was searched, and a total of 1,038 articles was used for the final analysis. Text network analysis and topic modeling were performed using Netminer 4.4 program.
Results: As a result of this study, the number of media reports related to nurses increased 3.86 times after the COVID-19 outbreak (6,197 cases) compared to before the COVID-19 outbreak (1,603 cases). As a result of topic modeling, four topics were derived before and after the COVID-19, respectively. Examples of topics were; Before the COVID-19 (‘a nurse who committed suicide because she could not withstand the Taewoom at work’, ‘a nurse as a perpetrator of the newborn abuse case’), and After the COVID-19 (‘a nurse as a victim of COVID-19’, ‘a nurse working with the support of the people’, ‘a nurse as a top contributor and a warrior to protect from COVID-19’).
Conclusion: Topics, derived by topic modelling, were changed more positively after the COVID-19, compared to before the COVID-19. It is suggested that continuous monitoring and further researches about the images of nurses should be performed by individual nurses and nursing organization.
|
|
|
KeyWords
|
|
COVID-19, 간호사, 대중매체, 이미지, 소셜 네트워크 분석
COVID-19, Nurses, Mass Media, Image, Social Network Analysis
|
|
|
원문 및 링크아웃 정보
|
|
|
|
|
등재저널 정보
|
|
   
|
|
|
|
|