빅데이터 기반의 커뮤니티케어 키워드 및 사회연결망분석
Communitycare Key words and Social Network Analysis based on Big Data
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참고문헌
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초록
This study is aimed at identifying trends in research on community care and the knowledge structure of community care related research in a research paper published in the journal 'community care', which is the policy of the Ministry of Health and Welfare in 2018, and through network analysis and connectivity analysis using Word2vec, the research trends of 'community care' are improved. In this study, keyword extraction and analysis were conducted using word-clouding of the Python program in the journal Community Care, and the data were collected using Word2Vec of Deep Learning Technique (RNN) for the centrality and cohesion analysis of Semantic network analysis. The results of the study are as follows. First, the words frequently appearing through word-clouding were in the order of 'service', 'care', 'community', 'social', 'the aged', 'region', 'research', 'welfare', ' facilities', 'an analysis' and 'policy'. Second, 'Service, 'Community', 'Care', 'Social', 'the aged' and 'research' were evaluated as the most important nodes after visualizing the network using the connection strength between words obtained from Word2vec for 50 major keywords of the frequency of emergence. The words 'build', 'social', 'institutional', 'recuperation', 'region', 'United Kingdom', 'policy', insurance' and 'disabled' were found to be highly interconnected. Third, based on the network model's assessment of the centrality, 'social ', 'United Kingdom' 'disabled', 'policy' and 'Korea' were found to have a high centrality, the words 'treatment', 'Korea' service', 'the aged' and 'recuperation' and 'nearly' words 'social' and 'system', 'United Kingdom' were investigated. Finally, the groupings of research subjects using intuitive clustering over the network confirmed that they were clustered into three groups: the service sector, the treatment, the center, and the policy and the plan, and the aspects of community and welfare were revealed.
Abstract
This study is aimed at identifying trends in research on community care and the knowledge structure of community care related research in a research paper published in the journal 'community care', which is the policy of the Ministry of Health and Welfare in 2018, and through network analysis and connectivity analysis using Word2vec, the research trends of 'community care' are improved. In this study, keyword extraction and analysis were conducted using word-clouding of the Python program in the journal Community Care, and the data were collected using Word2Vec of Deep Learning Technique (RNN) for the centrality and cohesion analysis of Semantic network analysis. The results of the study are as follows. First, the words frequently appearing through word-clouding were in the order of 'service', 'care', 'community', 'social', 'the aged', 'region', 'research', 'welfare', ' facilities', 'an analysis' and 'policy'. Second, 'Service, 'Community', 'Care', 'Social', 'the aged' and 'research' were evaluated as the most important nodes after visualizing the network using the connection strength between words obtained from Word2vec for 50 major keywords of the frequency of emergence. The words 'build', 'social', 'institutional', 'recuperation', 'region', 'United Kingdom', 'policy', insurance' and 'disabled' were found to be highly interconnected. Third, based on the network model's assessment of the centrality, 'social ', 'United Kingdom' 'disabled', 'policy' and 'Korea' were found to have a high centrality, the words 'treatment', 'Korea' service', 'the aged' and 'recuperation' and 'nearly' words 'social' and 'system', 'United Kingdom' were investigated. Finally, the groupings of research subjects using intuitive clustering over the network confirmed that they were clustered into three groups: the service sector, the treatment, the center, and the policy and the plan, and the aspects of community and welfare were revealed.
참고문헌 (25)
- 안명숙, "빅데이터를 활용한 다문화 핵심단어 및 네트워크 분석", 융복합지식학회논문지, 6(2), pp.67~76 (2018), 융복합지식학회
- Carley, K., "Coding choices for textual analysis: A comparision of content analysis and map analysis", Sociological Methodology, 23, pp.75~126 (1993)
- Editing Department, "Health Promotion Discussion through Community Care", Monthly Resident Autonomy, 83, pp.98~99 (2018), Ministry of Health
- Hansen, D., "Analysing Social Media Networks with Node XL: Insights from a Connected World" (2010), Morgan kaufmann
- 황미경, "커뮤니티 케어와 통합사례관리 연계 네트워크 실천 방안 연구", 한국케어매니지먼트 연구, (30), pp.161~184 (2019), 한국통합사례관리학회[DOI]
- 강현철, "지역자산을 활용한 커뮤니티케어 운영에 관한 탐색적 연구", 한국지적정보학회지, 21(1), pp.39~54 (2019), 한국지적정보학회[DOI]
- Kang, H. S., "The plan study of public rental housing community facility for activation of local community", Master, Architecture and Architectural Planning, pp.2016
- 강순주, "아파트 단지 내 커뮤니티 시설의 운영 실태와 거주 후 평가 - 전문관리자 운영의 대구 R아파트 단지를 중심으로-", 한국주거학회논문집, 21(4), pp.111~120 (2010), 한국주거학회
- Community care cases and implications in Japan, "Monthly Public Policy", 2019, 68~71
- 김찬우, "노인 돌봄 서비스 수요 추정관련 고찰", 사회복지정책, (34), pp.163~190 (2008), 한국사회복지정책학회[DOI]
- 김선아, "텍스트마이닝 기법을 활용한 다문화 미술교육 연구 동향 분석 연구", 다문화교육연구, 9(2), pp.203~227 (2016), 한국다문화교육학회[DOI]
- 공선희, "영국의 커뮤니티 케어 정책의 역사적 변천과 쟁점: 노인케어의 혼합경제를 중심으로", 한국노년학, 35(1), pp.79~98 (2015), 한국노년학회
- "2013 Annual Report" (2014)[URL]
- 권성철, "한국과 일본의 장기요양제도의 형성과 전개과정에 관한 비교 고찰", 일본문화연구, (69), pp.25~49 (2019), 동아시아일본학회[DOI]
- Lee, J. W., "A study on the community care need assessment for elderly n rural area of Gangwon province", Master, pp.2019
- 임혜원, "커뮤니티케어관점에서의 노인주거공간 디자인 활용요소 연구 : 중국 공동주택 토루 분석을 중심으로", 기초조형학연구, 19(6), pp.639~650 (2018), 한국기초조형학회[DOI]
- "Community integrated care basic plan" (2018)[URL]
- "1ST community care 2026 Vision Forum" (2019)[URL]
- 박영주, "커뮤니티 케어 제도 내 작업치료사의 역할에 대한 고찰", 대한작업치료학회지, 27(1), pp.103~113 (2019), 대한작업치료학회[DOI]
- Sebei, H., "Review of social media analytics process and big data pipeline", Social Network Analysis and Mining, 8(1), pp.1~28 (2018)
- 신수진, "사회관계망에서 매개 중심도 추정을 위한 효율적인 알고리즘", 정보처리학회 논문지, 4(1), pp.37~44 (2015), 한국정보처리학회[DOI]
- Soek, J. E., "Community care and long-term care policy issues", Monthly Welfare Trends, 238(8), pp.28~33 (2018)
- Song, T. M., "Social big data research methodology with R" (2016), Hannarae Academic
- 서동희, "고령시대 공공데이터기반 지역사회 보건-복지 돌봄 방안 모색 - 커뮤니티케어를 중심으로 -", 한국사회복지행정학, 21(1), pp.55~81 (2019), 한국사회복지행정학회[DOI]
- Yoon, H. Y., "Community care cases in Korea and overseas, implications of the meaning & Initiative", Release of the Society for Social Welfare Studies' Academic Conference for Criticism and Alternatives, pp.333~354 (2018)