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| Analyse Scientométrique× | Analyse de co-citation× | |
|---|---|---|
| Domaine≠ | Scientométrie | Bibliométrie |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1969 (term); 1963 (Price's foundational work) | 1973 |
| Auteur d'origine≠ | V. V. Nalimov and Z. M. Mulchenko (term coined); Derek J. de Solla Price (foundational methods) | Henry Small |
| Type≠ | Quantitative literature analysis | Method |
| Source fondatrice≠ | Nalimov, V. V., & Mulchenko, Z. M. (1969). Naukometriya: Izucheniye razvitiya nauki kak informatsionnogo protsessa [Scientometrics: The Study of the Development of Science as an Information Process]. Nauka. link ↗ | 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 | scientometrics, science of science, quantitative science studies, research evaluation analysis | co-citation mapping, historiograph, direct citation, citation pair analysis |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | Scientometric analysis applies statistical and computational methods to publication and citation data to measure the growth, structure, and impact of scientific fields. Drawing on databases such as Web of Science, Scopus, or OpenAlex, it quantifies output trends, identifies leading authors and institutions, maps intellectual networks, and evaluates research impact — transforming large bibliographic corpora into evidence-based portraits of how knowledge develops and spreads. | 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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