方法对比
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| PRISMA合规的共被引分析× | 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≠ | 2009–2021 (methodological combination emerged in the 2010s) | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| 提出者≠ | PRISMA: Moher et al. (2009), updated Page et al. (2021); Co-citation: Henry Small (1973) | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| 类型≠ | Systematic bibliometric review | Evidence synthesis methodology |
| 开创性文献≠ | Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, n71. DOI ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| 别名 | systematic co-citation review, PRISMA co-citation, co-citation analysis with PRISMA reporting, transparent co-citation analysis | SLR, systematic review, evidence synthesis review, structured literature review |
| 相关≠ | 6 | 5 |
| 摘要≠ | PRISMA-compliant co-citation analysis is a systematic bibliometric method that applies the PRISMA 2020 reporting framework to co-citation analysis. It identifies intellectual clusters in a research field by measuring how frequently pairs of documents are cited together, while ensuring full transparency of the literature search, screening decisions, and analytic choices through a pre-registered protocol and standardised flow diagram. | 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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