Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Anàlisi d'Evolució Temàtica per Talles Temporals× | Revisió sistemàtica de la literatura× | |
|---|---|---|
| Camp | Cienciometria | Cienciometria |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen≠ | 2011–2012 | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Autor original≠ | Cobo, López-Herrera, Herrera-Viedma & Herrera | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Tipus≠ | Longitudinal bibliometric analysis | Evidence synthesis methodology |
| Font seminal≠ | 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 ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Àlies | longitudinal thematic mapping, temporal thematic evolution, time-period thematic analysis, diachronic science mapping | SLR, systematic review, evidence synthesis review, structured literature review |
| Relacionats≠ | 6 | 5 |
| Resum≠ | 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. | A systematic literature review (SLR) is a structured, reproducible method for identifying, appraising, and synthesizing all relevant studies on a research question. Unlike a narrative review, it follows an explicit, pre-specified protocol — from database search strings through inclusion criteria to data extraction — so that the process is transparent, auditable, and replicable by other researchers. It is widely used in medicine, education, software engineering, and the social sciences to produce the most comprehensive possible evidence base on a topic. |
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