方法对比
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| 基于bibliometrix的快速文献回顾× | 系统性文献综述× | |
|---|---|---|
| 领域 | 科学计量学 | 科学计量学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 2017 (bibliometrix); rapid review practice established ~2010s | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| 提出者≠ | 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) |
| 类型≠ | Expedited evidence synthesis with computational bibliometric support | Evidence synthesis methodology |
| 开创性文献≠ | 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 ↗ |
| 别名 | bibliometrix rapid review, R-based rapid review, rapid bibliometric review, tool-assisted rapid synthesis | SLR, systematic review, evidence synthesis review, structured literature review |
| 相关 | 5 | 5 |
| 摘要≠ | 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. |
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