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| Phân tích tổng hợp có hỗ trợ VOSviewer× | Tổng quan tài liệu có hệ thống× | |
|---|---|---|
| Lĩnh vực | Trắc lượng khoa học | Trắc lượng khoa học |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 2010s (integration practice emerged after VOSviewer release in 2010) | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Người khởi xướng≠ | Workflow combining Glass (1976) meta-analysis with van Eck & Waltman (2010) VOSviewer | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Loại≠ | Tool-assisted evidence synthesis workflow | Evidence synthesis methodology |
| Công trình gốc≠ | 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 ↗ |
| Tên gọi khác | bibliometric-enhanced meta-analysis, VOSviewer meta-analysis workflow, science-mapping assisted meta-analysis, network-visualisation meta-analysis | SLR, systematic review, evidence synthesis review, structured literature review |
| Liên quan | 5 | 5 |
| Tóm tắt≠ | VOSviewer-assisted meta-analysis integrates the bibliometric network visualisation capabilities of VOSviewer into the literature identification and mapping phases of a standard meta-analysis. Before the statistical pooling of effect sizes begins, VOSviewer is used to visualise co-citation networks, keyword co-occurrence maps, and publication clusters, helping researchers comprehensively delineate the research field and identify all eligible primary studies for quantitative synthesis. | 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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