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| Часово-розрізний наукометричний аналіз× | Аналіз спільно вживаних слів× | |
|---|---|---|
| Галузь | Наукометрія | Наукометрія |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1980s–1990s | 1983 |
| Автор методу≠ | Derived from scientometrics tradition; temporal slicing formalized in longitudinal bibliometric studies from the 1980s onward | Michel Callon, Jean-Pierre Courtial, and colleagues |
| Тип≠ | Quantitative longitudinal analysis | Scientometric network analysis technique |
| Основоположне джерело≠ | Small, H. (1999). Visualizing science by citation mapping. Journal of the American Society for Information Science, 50(9), 799-813. link ↗ | Callon, M., Courtial, J. P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191–235. DOI ↗ |
| Інші назви | temporal scientometrics, period-based scientometric analysis, time-window scientometrics, longitudinal scientometric analysis | keyword co-occurrence analysis, co-word mapping, keyword co-word network, CWA |
| Пов'язані | 6 | 6 |
| Підсумок≠ | Time-sliced scientometric analysis divides a bibliographic corpus into discrete temporal windows — commonly five- or ten-year periods — and applies standard scientometric indicators (publication counts, citation rates, h-index, collaboration networks, keyword co-occurrence) within each slice. By comparing results across slices, researchers can reconstruct how a scientific field has grown, shifted focus, formed new collaborations, or declined in influence over time. The approach combines the rigor of quantitative scientometrics with an explicit longitudinal dimension. | Co-word analysis is a scientometric technique that quantifies how often pairs of keywords, subject terms, or title words appear together across a corpus of publications. By treating simultaneous occurrence as a proxy for conceptual relatedness, it constructs networks and clusters that reveal the intellectual structure, dominant themes, and emerging sub-fields of a research domain. |
| ScholarGateНабір даних ↗ |
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