빅데이터 분석을 통한 스트릿 댄스 연구의 지식체계
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김수연 | - |
dc.contributor.author | 박성진 | - |
dc.contributor.author | 이해준 | - |
dc.date.accessioned | 2024-05-14T08:00:36Z | - |
dc.date.available | 2024-05-14T08:00:36Z | - |
dc.date.issued | 2023-06 | - |
dc.identifier.issn | 1226-0258 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/119025 | - |
dc.description.abstract | The purpose of this study is to identify the overall trend of street dance research through big data analysis and to suggest values and directions for future research. From 2001 to March 2023, thesis and academic journal data on ‘street dance’ were collected, and descriptive statistics were created and visual data were derived through data processing and refinement using TEXTOM and UCINET6 programs. First, as a result of identifying trends by year, it was found that the number of studies, which increased slightly at the beginning of the study, increased explosively from 2017. Second, as a result of identifying the current status by subject, ‘Kookmin University’, ‘Hanyang University’, and ‘Sejong University’ showed the highest status in the order of school status. appeared high. Third, as a result of identifying the frequency of use of major keywords and the centrality between major keywords, the subjects of the study were ‘street dance’, ‘hip-hop dance’, ‘street dancer’, and ‘street dance major’ among a total of 44 keywords. Research purpose category was the highest in the order of ‘impact’, ‘development process’, ‘analysis’, and ‘relationship analysis’ among a total of 111 keywords. In addition, as a result of examining connection centrality, ‘influence’-‘street dance major college students’ appeared the highest. | - |
dc.format.extent | 14 | - |
dc.language | 한국어 | - |
dc.language.iso | KOR | - |
dc.publisher | 한국체육과학회 | - |
dc.title | 빅데이터 분석을 통한 스트릿 댄스 연구의 지식체계 | - |
dc.title.alternative | Knowledge system of Streetdance research through big data analysis | - |
dc.type | Article | - |
dc.publisher.location | 대한민국 | - |
dc.identifier.doi | 10.35159/kjss.2023.06.32.3.603 | - |
dc.identifier.bibliographicCitation | 한국체육과학회지, v.32, no.3, pp 603 - 616 | - |
dc.citation.title | 한국체육과학회지 | - |
dc.citation.volume | 32 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 603 | - |
dc.citation.endPage | 616 | - |
dc.type.docType | 정기학술지(Article(Perspective Article포함)) | - |
dc.identifier.kciid | ART002979396 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | kci | - |
dc.subject.keywordAuthor | Street dance | - |
dc.subject.keywordAuthor | Big Data Analysis | - |
dc.subject.keywordAuthor | Text Mining, Textom | - |
dc.identifier.url | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11447030 | - |
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