방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 주제 진화 분석× | 공동 인용 분석× | |
|---|---|---|
| 분야≠ | 과학계량학 | 계량서지학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2011 | 1973 |
| 창시자≠ | Manuel J. Cobo and colleagues (University of Granada) | Henry Small |
| 유형≠ | Quantitative bibliometric technique | Method |
| 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 ↗ | Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265–269. DOI ↗ |
| 별칭 | TEA, thematic development analysis, temporal thematic mapping, longitudinal theme analysis | co-citation mapping, historiograph, direct citation, citation pair analysis |
| 관련≠ | 6 | 5 |
| 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. | Co-citation analysis is a method that identifies the intellectual structure of a research domain by examining how frequently pairs of documents are cited together in other publications. When two papers are frequently cited together in the literature, they are considered co-cited, indicating they are conceptually related or influential within the same research community. Developed by Henry Small in 1973, co-citation analysis maps the 'invisible colleges' of science—networks of researchers working on related problems—and reveals how knowledge domains evolve over time. |
| ScholarGate데이터셋 ↗ |
|
|