方法对比
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| 时间切片主题演化分析× | 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≠ | 2011–2012 | 1969 (term coined); practice dates to 1920s–1930s |
| 提出者≠ | Cobo, López-Herrera, Herrera-Viedma & Herrera | Alan Pritchard (coined term); earlier quantitative work by Paul Otlet (1934) and S. C. Bradford (1934) |
| 类型≠ | Longitudinal bibliometric analysis | Quantitative literature analysis |
| 开创性文献≠ | Cobo, M. J., López-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 | longitudinal thematic mapping, temporal thematic evolution, time-period thematic analysis, diachronic science mapping | bibliometrics, bibliometric study, bibliometric mapping, publication analysis |
| 相关 | 6 | 6 |
| 摘要≠ | Time-sliced thematic evolution analysis is a bibliometric method that divides a corpus of publications into consecutive time windows and tracks how research themes emerge, consolidate, split, merge, or disappear across those periods. By applying co-word analysis and strategic-diagram mapping within each slice and then linking themes across slices, it reveals the intellectual trajectory of a research field over time. | 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 ↗ |
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