Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Análisis de Co-citación Asistido por bibliometrix× | Análisis Bibliométrico× | |
|---|---|---|
| Campo | Cienciometría | Cienciometría |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 2017 (bibliometrix implementation); 1973 (co-citation concept) | 1969 (term coined); practice dates to 1920s–1930s |
| Autor original≠ | Co-citation: Henry Small (1973); bibliometrix package: Massimo Aria & Corrado Cuccurullo (2017) | Alan Pritchard (coined term); earlier quantitative work by Paul Otlet (1934) and S. C. Bradford (1934) |
| Tipo≠ | Computational scientometric pipeline | Quantitative literature analysis |
| Fuente seminal≠ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. DOI ↗ | Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348–349. link ↗ |
| Alias | R bibliometrix co-citation, bibliometrix CCA, co-citation network analysis with bibliometrix, bibliometrix cocitation mapping | bibliometrics, bibliometric study, bibliometric mapping, publication analysis |
| Relacionados | 6 | 6 |
| Resumen≠ | bibliometrix-assisted co-citation analysis combines Henry Small's co-citation measure with the open-source R package bibliometrix to map the intellectual structure of a research field. When two documents are frequently cited together by third papers, they are considered intellectually linked; the bibliometrix package automates construction of the co-citation matrix, similarity normalization, community detection, and network visualization, turning raw bibliographic exports into interpretable science maps. | Bibliometric analysis applies statistical and mathematical methods to bibliographic records — publications, citations, authors, journals, and keywords — to measure and map the structure, output, and intellectual evolution of a research field. It is widely used to identify influential works, prolific authors, productive journals, collaboration networks, and emerging research themes across any academic discipline. |
| ScholarGateConjunto de datos ↗ |
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