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| Мрежов наукометричен анализ× | Анализ на съвместно цитиране× | |
|---|---|---|
| Област≠ | Наукометрия | Библиометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1965 (Price); computational refinement 2000s–2010s | 1973 |
| Създател≠ | Derek J. de Solla Price (network citation structure); Nees Jan van Eck & Ludo Waltman (computational network mapping) | Henry Small |
| Тип≠ | Quantitative bibliometric method | Method |
| Основополагащ източник≠ | van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. 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 ↗ |
| Други названия | scientometric network analysis, bibliometric network analysis, citation network scientometrics, science network mapping | co-citation mapping, historiograph, direct citation, citation pair analysis |
| Свързани≠ | 6 | 5 |
| Резюме≠ | Network-based scientometric analysis applies graph-theoretic methods to bibliographic data — publications, citations, authors, and keywords — to map the intellectual structure of a scientific field. By modeling documents or authors as nodes and their relationships (citations, co-authorships, co-word occurrences) as edges, it reveals clusters of knowledge, central actors, emerging topics, and the flow of ideas across disciplines. Tools such as VOSviewer, Gephi, and the R package bibliometrix are commonly used. | 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. |
| ScholarGateНабор от данни ↗ |
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