Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Сетевой наукометрический анализ× | Коворд-анализ× | |
|---|---|---|
| Область | Наукометрия | Наукометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1965 (Price); computational refinement 2000s–2010s | 1983 |
| Автор метода≠ | Derek J. de Solla Price (network citation structure); Nees Jan van Eck & Ludo Waltman (computational network mapping) | Michel Callon, Jean-Pierre Courtial, and colleagues |
| Тип≠ | Quantitative bibliometric method | Scientometric network analysis technique |
| Основополагающий источник≠ | van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. DOI ↗ | Callon, M., Courtial, J. P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191–235. DOI ↗ |
| Другие названия | scientometric network analysis, bibliometric network analysis, citation network scientometrics, science network mapping | keyword co-occurrence analysis, co-word mapping, keyword co-word network, CWA |
| Связанные | 6 | 6 |
| Сводка≠ | 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-word analysis is a scientometric technique that quantifies how often pairs of keywords, subject terms, or title words appear together across a corpus of publications. By treating simultaneous occurrence as a proxy for conceptual relatedness, it constructs networks and clusters that reveal the intellectual structure, dominant themes, and emerging sub-fields of a research domain. |
| ScholarGateНабор данных ↗ |
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