方法对比
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| 时间切片主题演化分析× | 主题演化分析× | |
|---|---|---|
| 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 | 2011 |
| 提出者≠ | Cobo, López-Herrera, Herrera-Viedma & Herrera | Manuel J. Cobo and colleagues (University of Granada) |
| 类型≠ | Longitudinal bibliometric analysis | Quantitative bibliometric technique |
| 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 ↗ | 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 ↗ |
| 别名 | longitudinal thematic mapping, temporal thematic evolution, time-period thematic analysis, diachronic science mapping | TEA, thematic development analysis, temporal thematic mapping, longitudinal theme 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. | 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. |
| ScholarGate数据集 ↗ |
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