Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Прискорений огляд за допомогою bibliometrix× | Систематичний огляд літератури× | |
|---|---|---|
| Галузь | Наукометрія | Наукометрія |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 2017 (bibliometrix); rapid review practice established ~2010s | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Автор методу≠ | Aria & Cuccurullo (bibliometrix package); rapid review tradition from Cochrane and evidence synthesis community | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Тип≠ | Expedited evidence synthesis with computational bibliometric support | Evidence synthesis methodology |
| Основоположне джерело≠ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. DOI ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Інші назви | bibliometrix rapid review, R-based rapid review, rapid bibliometric review, tool-assisted rapid synthesis | SLR, systematic review, evidence synthesis review, structured literature review |
| Пов'язані | 5 | 5 |
| Підсумок≠ | A bibliometrix-assisted rapid review combines the speed and pragmatic focus of a rapid review with the computational power of the bibliometrix R package. Researchers use bibliometrix to automate citation import, deduplication, descriptive statistics, and science-mapping tasks, compressing the bibliometric phase of a rapid review from days to hours while maintaining transparent, reproducible workflows within a single open-source environment. | 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. |
| ScholarGateНабір даних ↗ |
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