Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchambuzi wa Meta-Uliofanywa kwa Msaada wa VOSviewer× | Ramani ya Kisayansi× | |
|---|---|---|
| Nyanja≠ | Saintometriki | Bibliometriki |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 2010s (integration practice emerged after VOSviewer release in 2010) | 2000s |
| Mwanzilishi≠ | Workflow combining Glass (1976) meta-analysis with van Eck & Waltman (2010) VOSviewer | Katy Börner, Chaomei Chen, and others |
| Aina≠ | Tool-assisted evidence synthesis workflow | Method |
| Chanzo asilia≠ | van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. DOI ↗ | Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255. DOI ↗ |
| Majina mbadala≠ | bibliometric-enhanced meta-analysis, VOSviewer meta-analysis workflow, science-mapping assisted meta-analysis, network-visualisation meta-analysis | knowledge mapping, domain mapping, research landscape visualization |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | 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. | Science mapping is a bibliometric visualization method that creates visual representations of research domains, showing the structure, development, and relationships of scientific fields. Using bibliographic data (citations, keywords, authors, journals), science mapping algorithms generate network diagrams where nodes represent documents, concepts, or authors and edges represent relationships (citation, collaboration, semantic similarity). The resulting maps make invisible intellectual structures visible, enabling researchers to understand field topology, identify emerging areas, and navigate disciplinary landscapes. Pioneered by Börner, Chen, and Boyack in the 2000s, science mapping has become a standard tool in research evaluation and strategic planning. |
| ScholarGateSeti ya data ↗ |
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