Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Систематический обзор литературы с использованием библиометрического анализа× | Картографирование науки (Science Mapping)× | |
|---|---|---|
| Область≠ | Наукометрия | Библиометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2017 | 2000s |
| Автор метода≠ | Massimo Aria & Corrado Cuccurullo (bibliometrix R package) | Katy Börner, Chaomei Chen, and others |
| Тип≠ | Software-assisted systematic review | Method |
| Основополагающий источник≠ | 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 ↗ |
| Другие названия≠ | bibliometrix SLR, R-bibliometrix systematic review, bibliometrix-based literature review, bibliometrix-enhanced SLR | knowledge mapping, domain mapping, research landscape visualization |
| Связанные≠ | 6 | 5 |
| Сводка≠ | A bibliometrix-assisted systematic literature review integrates the R package bibliometrix — developed by Aria and Cuccurullo (2017) — into the standard systematic review pipeline to automate and visualize bibliometric performance and science-mapping analyses. It combines the transparency and reproducibility of a protocol-driven systematic search with quantitative tools for tracking publication trends, author collaboration networks, keyword co-occurrence, and thematic evolution across a field. | 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. |
| ScholarGateНабор данных ↗ |
|
|