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| 시간 분할 인용 분석× | 주제 진화 분석× | |
|---|---|---|
| 분야 | 과학계량학 | 과학계량학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1955–1965 (foundational); temporal slicing formalized in scientometrics from the 1980s onward | 2011 |
| 창시자≠ | Eugene Garfield (citation analysis foundation); Derek J. de Solla Price (temporal/longitudinal framing) | Manuel J. Cobo and colleagues (University of Granada) |
| 유형≠ | Quantitative scientometric technique | Quantitative bibliometric technique |
| 원전≠ | Garfield, E. (1955). Citation indexes for science: A new dimension in documentation through association of ideas. Science, 122(3159), 108–111. DOI ↗ | Cobo, M. J., Lopez-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382–1402. DOI ↗ |
| 별칭 | temporal citation analysis, longitudinal citation analysis, time-window citation analysis, diachronic citation analysis | TEA, thematic development analysis, temporal thematic mapping, longitudinal theme analysis |
| 관련 | 6 | 6 |
| 요약≠ | Time-sliced citation analysis partitions a body of literature into sequential temporal windows — for example, five-year intervals — and performs citation analysis within and across each window. This reveals how citation patterns, influential papers, and knowledge flows shift over time, providing a dynamic picture of a field's intellectual evolution rather than a static aggregate snapshot. | Thematic evolution analysis is a bibliometric technique that divides a body of literature into consecutive time periods and tracks how research themes emerge, consolidate, split, merge, or disappear across those periods. By combining co-word analysis, clustering, and strategic diagrams for each time slice, it produces a dynamic picture of a field's intellectual development rather than a static snapshot. |
| ScholarGate데이터셋 ↗ |
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