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| Revue systématique de littérature à tranches temporelles× | Analyse de co-citation× | |
|---|---|---|
| Domaine≠ | Scientométrie | Bibliométrie |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 2010s | 1973 |
| Auteur d'origine≠ | Adapted from systematic review methodology; temporal segmentation formalized in bibliometric practice (Zupic & Cater, 2015; Aria & Cuccurullo, 2017) | Henry Small |
| Type≠ | Systematic review variant with temporal segmentation | Method |
| Source fondatrice≠ | Zupic, I., & Cater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3), 429–472. 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 | temporal systematic review, period-based systematic review, chronological systematic review, time-segmented literature review | co-citation mapping, historiograph, direct citation, citation pair analysis |
| Apparentées | 5 | 5 |
| Résumé≠ | A time-sliced systematic literature review applies the rigorous search, screening, and synthesis protocol of a standard systematic review while dividing the retrieved corpus into discrete temporal periods — time slices — and analyzing each period separately. This design reveals how a research field has developed across time: which topics emerged, grew, or declined; how key authors and journals shifted; and how intellectual structures evolved from one era to the next. | 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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