Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Прискорений огляд за допомогою bibliometrix× | Картографування науки× | |
|---|---|---|
| Галузь≠ | Наукометрія | Бібліометрія |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 2017 (bibliometrix); rapid review practice established ~2010s | 2000s |
| Автор методу≠ | Aria & Cuccurullo (bibliometrix package); rapid review tradition from Cochrane and evidence synthesis community | Katy Börner, Chaomei Chen, and others |
| Тип≠ | Expedited evidence synthesis with computational bibliometric support | Method |
| Основоположне джерело≠ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. DOI ↗ | Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255. DOI ↗ |
| Інші назви≠ | bibliometrix rapid review, R-based rapid review, rapid bibliometric review, tool-assisted rapid synthesis | knowledge mapping, domain mapping, research landscape visualization |
| Пов'язані | 5 | 5 |
| Підсумок≠ | 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. | 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. |
| ScholarGateНабір даних ↗ |
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