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| Systematyczny przegląd literatury wspomagany przez VOSviewer× | Przegląd literatury systematyczny× | |
|---|---|---|
| Dziedzina | Naukometria | Naukometria |
| Rodzina | Process / pipeline | Process / pipeline |
| Rok powstania≠ | 2010 (VOSviewer); practice established circa 2012–2015 | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Twórca≠ | van Eck & Waltman (VOSviewer tool); combined with Kitchenham SLR guidelines | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Typ≠ | Mixed bibliometric-qualitative review method | Evidence synthesis methodology |
| Źródło pierwotne≠ | 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 ↗ |
| Inne nazwy | VOSviewer SLR, bibliometric-enhanced systematic review, VOSviewer-integrated review, visualization-assisted SLR | SLR, systematic review, evidence synthesis review, structured literature review |
| Pokrewne≠ | 6 | 5 |
| Podsumowanie≠ | A VOSviewer-assisted systematic literature review combines the rigorous search-and-appraisal pipeline of a standard systematic review with bibliometric network visualization produced by the VOSviewer software. The approach allows researchers to systematically retrieve and screen the literature while simultaneously mapping co-citation clusters, keyword co-occurrence networks, and institutional collaboration patterns, yielding both a narrative synthesis and a visual, quantitative overview of the field's intellectual structure. | 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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