Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| VOSviewer и CiteSpace: инструменты для библиометрического анализа и визуализации× | Картографирование науки (Science Mapping)× | |
|---|---|---|
| Область | Библиометрия | Библиометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2006–2010 | 2000s |
| Автор метода≠ | Nees Jan van Eck & Ludo Waltman (VOSviewer); Chaomei Chen (CiteSpace) | Katy Börner, Chaomei Chen, and others |
| Тип≠ | Tool | Method |
| Основополагающий источник≠ | Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. DOI ↗ | Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255. DOI ↗ |
| Другие названия | bibliometric mapping software, citation visualization tools, science mapping tools | knowledge mapping, domain mapping, research landscape visualization |
| Связанные≠ | 4 | 5 |
| Сводка≠ | VOSviewer and CiteSpace are specialized software tools designed to conduct bibliometric analysis and create science maps from research literature. VOSviewer (developed by Van Eck & Waltman, 2010) excels at creating publication landscapes through co-occurrence, co-citation, and bibliographic coupling analysis with intuitive visual output. CiteSpace (developed by Chaomei Chen, 2006) focuses on detecting emerging research trends and research fronts through direct citation analysis and specialized temporal algorithms. Together, these tools democratized science mapping, enabling researchers without programming expertise to visualize research domains comprehensively. | Science mapping is a bibliometric visualization method that creates visual representations of research domains, showing the structure, development, and relationships of scientific fields. Using bibliographic data (citations, keywords, authors, journals), science mapping algorithms generate network diagrams where nodes represent documents, concepts, or authors and edges represent relationships (citation, collaboration, semantic similarity). The resulting maps make invisible intellectual structures visible, enabling researchers to understand field topology, identify emerging areas, and navigate disciplinary landscapes. Pioneered by Börner, Chen, and Boyack in the 2000s, science mapping has become a standard tool in research evaluation and strategic planning. |
| ScholarGateНабор данных ↗ |
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