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| Anàlisi bibliomètrica per tall temporal× | Anàlisi d'evolució temàtica× | |
|---|---|---|
| Camp | Cienciometria | Cienciometria |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen≠ | 2000s–2010s (as an explicit methodological variant) | 2011 |
| Autor original≠ | Derived from classical bibliometrics (Price, Garfield); explicitly formalised in longitudinal studies by Zhao & Strotmann (2008) and others | Manuel J. Cobo and colleagues (University of Granada) |
| Tipus≠ | Quantitative scientometric analysis | Quantitative bibliometric technique |
| Font seminal≠ | Zhao, D., & Strotmann, A. (2008). Evolution of research activities and intellectual influences in information science 1996–2005: Introducing author bibliographic-coupling analysis. Journal of the American Society for Information Science and Technology, 59(13), 2070–2086. 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 ↗ |
| Àlies | longitudinal bibliometrics, temporal bibliometric analysis, diachronic bibliometrics, time-window bibliometric analysis | TEA, thematic development analysis, temporal thematic mapping, longitudinal theme analysis |
| Relacionats | 6 | 6 |
| Resum≠ | Time-sliced bibliometric analysis partitions a literature corpus into consecutive time windows and applies standard bibliometric indicators (publication counts, citation patterns, co-authorship networks, keyword frequencies) within each window. By comparing results across slices, researchers can document how a field's productivity, intellectual structure, and thematic focus have shifted over time — providing a diachronic rather than static view of scholarly output. | 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. |
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