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| 주제 진화 분석× | 계량서지 분석× | |
|---|---|---|
| 분야 | 과학계량학 | 과학계량학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2011 | 1969 (term coined); practice dates to 1920s–1930s |
| 창시자≠ | Manuel J. Cobo and colleagues (University of Granada) | Alan Pritchard (coined term); earlier quantitative work by Paul Otlet (1934) and S. C. Bradford (1934) |
| 유형≠ | Quantitative bibliometric technique | Quantitative literature analysis |
| 원전≠ | 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 ↗ | Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348–349. link ↗ |
| 별칭 | TEA, thematic development analysis, temporal thematic mapping, longitudinal theme analysis | bibliometrics, bibliometric study, bibliometric mapping, publication analysis |
| 관련 | 6 | 6 |
| 요약≠ | 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. | 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. |
| ScholarGate데이터셋 ↗ |
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