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KMID : 1155220210460030257
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Journal of the Korean Society of Health Information and Health Statistics
2021 Volume.46 No. 3 p.257 ~ p.266
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Keyword Network Analysis on Long Term Care Insurance Using Text Mining
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Abstract
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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.
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KEYWORD
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Text mining, Big data, Keyword network, Long term care, News article
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FullTexts / Linksout information
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Listed journal information
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