Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Análisis de Citas Asistido por Bibliometrix× | Mapeo de la Ciencia× | |
|---|---|---|
| Campo≠ | Cienciometría | Bibliometría |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 2017 (bibliometrix package); citation analysis since 1955 | 2000s |
| Autor original≠ | Massimo Aria & Corrado Cuccurullo (bibliometrix R package); citation analysis concepts from Eugene Garfield (1955) | Katy Börner, Chaomei Chen, and others |
| Tipo≠ | Quantitative bibliometric pipeline | Method |
| Fuente seminal≠ | 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 ↗ |
| Alias≠ | bibliometrix citation analysis, R-based citation analysis, bibliometrix CA, citation analysis with bibliometrix | knowledge mapping, domain mapping, research landscape visualization |
| Relacionados≠ | 6 | 5 |
| Resumen≠ | Bibliometrix-assisted citation analysis uses the bibliometrix R package to systematically retrieve, clean, and analyze citation data exported from major databases such as Web of Science and Scopus. By automating reference parsing, frequency counting, and network construction, it enables researchers to identify the most-cited works, map intellectual influence, and trace the evolution of scholarly fields at a scale that manual analysis cannot match. | 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. |
| ScholarGateConjunto de datos ↗ |
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