مقایسهٔ روشها
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| مرور نقشهبرداری با کمک کتابسنجی (bibliometrix-Assisted Mapping Review)× | مرور نظاممند ادبیات× | |
|---|---|---|
| حوزه | علمسنجی | علمسنجی |
| خانواده | Process / pipeline | Process / pipeline |
| سال پیدایش≠ | 2017 (bibliometrix tool); mapping review approach formalised c. 2010s | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| پدیدآور≠ | Aria & Cuccurullo (bibliometrix, 2017); mapping review methodology developed in evidence synthesis community (~2000s) | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| نوع≠ | Tool-assisted evidence mapping review | Evidence synthesis methodology |
| منبع بنیادین≠ | 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 ↗ |
| نامهای دیگر | bibliometrix mapping review, R-bibliometrix evidence map, bibliometric-assisted systematic map, bibliometrix evidence synthesis map | SLR, systematic review, evidence synthesis review, structured literature review |
| مرتبط | 5 | 5 |
| خلاصه≠ | A bibliometrix-assisted mapping review combines the structured scope-and-search logic of an evidence mapping review with the analytical power of the bibliometrix R package. Instead of manually categorising studies, the researcher leverages bibliometrix functions — keyword co-occurrence networks, thematic clustering, and yearly trend analysis — to chart the landscape of a research field systematically and at scale, producing an interactive, reproducible evidence map. | 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. |
| ScholarGateمجموعهداده ↗ |
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