Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Систематичен литературен преглед, подпомогнат от bibliometrix× | Научно картографиране× | |
|---|---|---|
| Област≠ | Наукометрия | Библиометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 2017 | 2000s |
| Създател≠ | Massimo Aria & Corrado Cuccurullo (bibliometrix R package) | Katy Börner, Chaomei Chen, and others |
| Тип≠ | Software-assisted systematic review | Method |
| Основополагащ източник≠ | 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 ↗ |
| Други названия≠ | bibliometrix SLR, R-bibliometrix systematic review, bibliometrix-based literature review, bibliometrix-enhanced SLR | knowledge mapping, domain mapping, research landscape visualization |
| Свързани≠ | 6 | 5 |
| Резюме≠ | 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 от данни ↗ |
|
|