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| 시간 분할 계량정보 분석× | 계량서지 분석× | |
|---|---|---|
| 분야 | 과학계량학 | 과학계량학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1980s–1990s | 1969 (term coined); practice dates to 1920s–1930s |
| 창시자≠ | Derived from scientometrics tradition; temporal slicing formalized in longitudinal bibliometric studies from the 1980s onward | Alan Pritchard (coined term); earlier quantitative work by Paul Otlet (1934) and S. C. Bradford (1934) |
| 유형≠ | Quantitative longitudinal analysis | Quantitative literature analysis |
| 원전≠ | Small, H. (1999). Visualizing science by citation mapping. Journal of the American Society for Information Science, 50(9), 799-813. link ↗ | Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348–349. link ↗ |
| 별칭 | temporal scientometrics, period-based scientometric analysis, time-window scientometrics, longitudinal scientometric analysis | bibliometrics, bibliometric study, bibliometric mapping, publication analysis |
| 관련 | 6 | 6 |
| 요약≠ | Time-sliced scientometric analysis divides a bibliographic corpus into discrete temporal windows — commonly five- or ten-year periods — and applies standard scientometric indicators (publication counts, citation rates, h-index, collaboration networks, keyword co-occurrence) within each slice. By comparing results across slices, researchers can reconstruct how a scientific field has grown, shifted focus, formed new collaborations, or declined in influence over time. The approach combines the rigor of quantitative scientometrics with an explicit longitudinal dimension. | 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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