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텍스트마이닝을 통한 노인장기요양보험 키워드 네트워크 분석
DC Field | Value | Language |
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dc.contributor.author | 김태현 | - |
dc.contributor.author | 남정모 | - |
dc.contributor.author | 박소희 | - |
dc.date.accessioned | 2022-09-14T01:28:35Z | - |
dc.date.available | 2022-09-14T01:28:35Z | - |
dc.date.issued | 2021-08 | - |
dc.identifier.issn | 2287-3708 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/190470 | - |
dc.description.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. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | Korean | - |
dc.publisher | 한국보건정보통계학회 | - |
dc.relation.isPartOf | Journal of Health Informatics and Statistics(보건정보통계학회지) | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | 텍스트마이닝을 통한 노인장기요양보험 키워드 네트워크 분석 | - |
dc.type | Article | - |
dc.contributor.college | Graduate School of Public Health (보건대학원) | - |
dc.contributor.department | Graduate School of Public Health (보건대학원) | - |
dc.contributor.googleauthor | 서종근 | - |
dc.contributor.googleauthor | 남정모 | - |
dc.contributor.googleauthor | 김태현 | - |
dc.contributor.googleauthor | 박소희 | - |
dc.identifier.doi | 10.21032/jhis.2021.46.3.257 | - |
dc.contributor.localId | A01082 | - |
dc.contributor.localId | A01264 | - |
dc.contributor.localId | A01531 | - |
dc.relation.journalcode | J01433 | - |
dc.subject.keyword | Text mining | - |
dc.subject.keyword | Big data | - |
dc.subject.keyword | Keyword network | - |
dc.subject.keyword | Long term care | - |
dc.subject.keyword | News article | - |
dc.contributor.alternativeName | Kim, Tae Hyun | - |
dc.contributor.affiliatedAuthor | 김태현 | - |
dc.contributor.affiliatedAuthor | 남정모 | - |
dc.contributor.affiliatedAuthor | 박소희 | - |
dc.citation.volume | 46 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 257 | - |
dc.citation.endPage | 266 | - |
dc.identifier.bibliographicCitation | Journal of Health Informatics and Statistics (보건정보통계학회지), Vol.46(3) : 257-266, 2021-08 | - |
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