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| bibliometrix 기반 과학 지도 제작× | 계량서지 분석× | |
|---|---|---|
| 분야 | 과학계량학 | 과학계량학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2017 | 1969 (term coined); practice dates to 1920s–1930s |
| 창시자≠ | Massimo Aria & Corrado Cuccurullo (bibliometrix R package) | Alan Pritchard (coined term); earlier quantitative work by Paul Otlet (1934) and S. C. Bradford (1934) |
| 유형≠ | Computational bibliometric pipeline | Quantitative literature analysis |
| 원전≠ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. DOI ↗ | Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348–349. link ↗ |
| 별칭 | bibliometrix science mapping, R-based science mapping, bibliometrix bibliometric mapping, bibliometrix-driven knowledge mapping | bibliometrics, bibliometric study, bibliometric mapping, publication analysis |
| 관련 | 6 | 6 |
| 요약≠ | bibliometrix-assisted science mapping is a computational approach that uses the bibliometrix R package to retrieve, clean, and analyze large bibliographic datasets, producing structured visual maps of how knowledge in a field is organized, interconnected, and evolving over time. It combines descriptive bibliometrics with network analysis and strategic clustering techniques to reveal intellectual structure, thematic frontiers, and influential actors in a research domain. | Bibliometric analysis applies statistical and mathematical methods to bibliographic records — publications, citations, authors, journals, and keywords — to measure and map the structure, output, and intellectual evolution of a research field. It is widely used to identify influential works, prolific authors, productive journals, collaboration networks, and emerging research themes across any academic discipline. |
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