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| Analyse Scientométrique Assistée par bibliometrix× | Analyse de co-citation× | |
|---|---|---|
| Domaine≠ | Scientométrie | Bibliométrie |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 2017 (bibliometrix package); scientometrics as a field: 1969 | 1973 |
| Auteur d'origine≠ | Massimo Aria & Corrado Cuccurullo (bibliometrix package); scientometrics founded by Derek J. de Solla Price | Henry Small |
| Type≠ | Quantitative literature analysis workflow | Method |
| Source fondatrice≠ | 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 ↗ |
| Alias | bibliometrix scientometrics, R-based scientometric analysis, bibliometrix workflow, science-of-science analysis with bibliometrix | co-citation mapping, historiograph, direct citation, citation pair analysis |
| Apparentées | 5 | 5 |
| Résumé≠ | 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. |
| ScholarGateJeu de données ↗ |
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