Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Подпомогнат от VOSviewer обзор на обхвата× | Систематичен литературен обзор× | |
|---|---|---|
| Област | Наукометрия | Наукометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 2010s–present | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Създател≠ | Combination: Arksey & O'Malley (scoping review, 2005); van Eck & Waltman (VOSviewer, 2010) | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Тип≠ | Hybrid review methodology | Evidence synthesis methodology |
| Основополагащ източник≠ | van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. DOI ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Други названия | VOSviewer scoping review, bibliometric-enhanced scoping review, VOS-assisted scoping review, science-mapping scoping review | SLR, systematic review, evidence synthesis review, structured literature review |
| Свързани | 5 | 5 |
| Резюме≠ | A VOSviewer-assisted scoping review integrates the structured, broad-mapping purpose of a scoping review with VOSviewer's bibliometric visualization capabilities. After standard database searching and eligibility screening, the retained records are exported to VOSviewer, which produces co-authorship, keyword co-occurrence, and citation-based cluster maps. These visual outputs guide thematic synthesis, reveal intellectual structure, and make the scope of a field immediately transparent. | 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. |
| ScholarGateНабор от данни ↗ |
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