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| Analiza Scienometryczna Wspomagana Bibliometrix× | Analiza współcytowań× | |
|---|---|---|
| Dziedzina≠ | Naukometria | Bibliometria |
| Rodzina | Process / pipeline | Process / pipeline |
| Rok powstania≠ | 2017 (bibliometrix package); scientometrics as a field: 1969 | 1973 |
| Twórca≠ | Massimo Aria & Corrado Cuccurullo (bibliometrix package); scientometrics founded by Derek J. de Solla Price | Henry Small |
| Typ≠ | Quantitative literature analysis workflow | Method |
| Źródło pierwotne≠ | 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 ↗ |
| Inne nazwy | bibliometrix scientometrics, R-based scientometric analysis, bibliometrix workflow, science-of-science analysis with bibliometrix | co-citation mapping, historiograph, direct citation, citation pair analysis |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | bibliometrix-assisted scientometric analysis is a reproducible, R-based workflow that applies the bibliometrix package to analyse the structure and dynamics of scientific fields using publication metadata. It integrates descriptive statistics, citation metrics, and network analysis — co-citation, bibliographic coupling, co-authorship, and co-word — into a single scriptable environment, enabling systematic, transparent mapping of research landscapes at scale. | 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. |
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