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| bibliometrix-támogatott együtt-idézési elemzés× | Ko-idézéselemzés× | |
|---|---|---|
| Tudományterület≠ | Tudománymetria | Bibliometria |
| Módszercsalád | Process / pipeline | Process / pipeline |
| Keletkezés éve≠ | 2017 (bibliometrix implementation); 1973 (co-citation concept) | 1973 |
| Megalkotó≠ | Co-citation: Henry Small (1973); bibliometrix package: Massimo Aria & Corrado Cuccurullo (2017) | Henry Small |
| Típus≠ | Computational scientometric pipeline | Method |
| Alapmű≠ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. DOI ↗ | Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265–269. DOI ↗ |
| Alternatív nevek | R bibliometrix co-citation, bibliometrix CCA, co-citation network analysis with bibliometrix, bibliometrix cocitation mapping | co-citation mapping, historiograph, direct citation, citation pair analysis |
| Kapcsolódó≠ | 6 | 5 |
| Összefoglaló≠ | 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. | Co-citation analysis is a method that identifies the intellectual structure of a research domain by examining how frequently pairs of documents are cited together in other publications. When two papers are frequently cited together in the literature, they are considered co-cited, indicating they are conceptually related or influential within the same research community. Developed by Henry Small in 1973, co-citation analysis maps the 'invisible colleges' of science—networks of researchers working on related problems—and reveals how knowledge domains evolve over time. |
| ScholarGateAdatkészlet ↗ |
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