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텍스트마이닝을 통한 노인장기요양보험 키워드 네트워크 분석

Authors
 서종근  ;  남정모  ;  김태현  ;  박소희 
Citation
 Journal of Health Informatics and Statistics (보건정보통계학회지), Vol.46(3) : 257-266, 2021-08 
Journal Title
Journal of Health Informatics and Statistics(보건정보통계학회지)
ISSN
 2287-3708 
Issue Date
2021-08
Keywords
Text mining ; Big data ; Keyword network ; Long term care ; News article
Abstract
Objectives
This study conducted research using big data in order to overcome the limitations of existing qualitative research or analysis research. By analyzing keywords, the flow and role of long-term care insurance in society were analyzed.
Methods
Issues were searched through text mining, one of the big data techniques, and the flow of agendas by period was examined by 3 time points (institutional settlement period, 1st basic plan, 2nd basic plan). Using R and NetMiner, Daum News (news.daum.net) and Naver News (news.naver.com) were web-scraped to collect 20,965 news articles, 4,994 articles were filtered for keyword extraction and analysis. Result: Looking at the characteristics of each data type, in all data types, long-term care institutions (including nursing homes) and care providers appear as the top keywords, and the keyword subgroup characteristics are ① grade/service, ② institution management, and ③ the employee group includes the keyword subgroup.
Conclusions
This study is based on the subject of long-term care insurance for the elderly and applies big data analysis techniques, and can be used as a decision-making tool in establishing policies and systems.
Files in This Item:
T202126093.pdf Download
DOI
10.21032/jhis.2021.46.3.257
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Preventive Medicine (예방의학교실) > 1. Journal Papers
4. Graduate School of Public Health (보건대학원) > Graduate School of Public Health (보건대학원) > 1. Journal Papers
Yonsei Authors
Kim, Tae Hyun(김태현) ORCID logo https://orcid.org/0000-0003-1053-8958
Nam, Chung Mo(남정모) ORCID logo https://orcid.org/0000-0003-0985-0928
Park, So Hee(박소희) ORCID logo https://orcid.org/0000-0001-8513-5163
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/190470
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