方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 主题演化分析× | 文献计量分析× | |
|---|---|---|
| 领域 | 科学计量学 | 科学计量学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 2011 | 1969 (term coined); practice dates to 1920s–1930s |
| 提出者≠ | Manuel J. Cobo and colleagues (University of Granada) | Alan Pritchard (coined term); earlier quantitative work by Paul Otlet (1934) and S. C. Bradford (1934) |
| 类型≠ | Quantitative bibliometric technique | Quantitative literature analysis |
| 开创性文献≠ | 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 ↗ |
| 别名 | TEA, thematic development analysis, temporal thematic mapping, longitudinal theme analysis | bibliometrics, bibliometric study, bibliometric mapping, publication analysis |
| 相关 | 6 | 6 |
| 摘要≠ | 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. |
| ScholarGate数据集 ↗ |
|
|