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소셜 빅데이터 기반 보건복지 정책 미래신호 예측 = Future Signals of Health and Welfare Policies and Issues using Social Big Data

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dc.contributor.author송태민
dc.contributor.author송주영
dc.date.accessioned2017-01-25T04:07:34Z
dc.date.available2017-01-25T04:07:34Z
dc.date.issued2016-11-28
dc.identifier.issn2465-8014
dc.identifier.urihttps://repository.kihasa.re.kr/handle/201002/24888
dc.description.abstractObjectives: The purpose of this study is to collect health and welfare-related documents mentioned in and collectable from online channels, analyze important health and welfare keywords through topic and sentimental analyses, detect future signals concerning major policies and issues related to health and welfare services, and propose a prediction model. Methods: 201,849 Health & Welfare related online documents from January 1 to March 31, 2016 from 171 Korean online channels and analyzed such documents using machine learning with random forest and Apriori algorithm association analysis. We used R software (version 3.2.1) for the association analysis data mining and visualization. Results: As for the prediction of future signals of health and welfare policies, policies that were important and supported by the people were welfare payment, health promotion, job, marriage/child birth, health insurance, and healthcare industry (in this order). Specifically, as support for documents mentioning welfare payment and jobs was high, job creation through building a spontaneous welfare system is thought to be needed. Additionally, similar to the linkage analysis result of policies, as people were against documents that mentioned only {basic pension} policies, but supported documents that included {basic pension, welfare payment, job}, there is a strong demand for the establishment of a welfare system through active self-support and labor of the elderly. Conclusions: Social big data can be utilized in various areas. First, similar to the application in this study, future signals concerning government`s policies and new technologies can be predicted in advance and prepared for. Second, they can be used as a new data collection methods that supplement limitations in survey data collection systems. Finally, a preemptive response system against risk can be established through monitoring and predicting social crisis.
dc.format.extent11
dc.languagekor
dc.publisher한국보건정보통계학회
dc.title소셜 빅데이터 기반 보건복지 정책 미래신호 예측
dc.title.alternativeFuture Signals of Health and Welfare Policies and Issues using Social Big Data
dc.typeArticle
dc.type.localArticle(Academic)
dc.identifier.apprname학술논문평가
dc.subject.keywordSocial big data
dc.subject.keywordMachine learning
dc.subject.keywordFuture signals
dc.subject.keywordHealth&welfare
dc.contributor.affiliatedAuthor송태민
dc.identifier.doi10.21032/jhis.2016.41.4.418
dc.identifier.urlhttps://doi.org/10.21032/jhis.2016.41.4.418
dc.citation.title보건정보통계학회지
dc.citation.volume41
dc.citation.number4
dc.citation.startPage417
dc.citation.endPage427
dc.identifier.bibliographicCitation보건정보통계학회지, vol. 41, no. 4, pp. 417 - 427
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