Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Quadruple Helix Analysis× | Картографирование науки (Science Mapping)× | |
|---|---|---|
| Область≠ | Science Technology Studies | Библиометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2009 | 2000s |
| Автор метода≠ | Elias Carayannis & David Campbell (Quadruple Helix); Loet Leydesdorff (N-tuple formalisation) | Katy Börner, Chaomei Chen, and others |
| Тип≠ | Innovation-ecosystem framework | Method |
| Основополагающий источник≠ | Carayannis, E. G., & Campbell, D. F. J. (2009). 'Mode 3' and 'Quadruple Helix': toward a 21st century fractal innovation ecosystem. International Journal of Technology Management, 46(3-4), 201-234. 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 | Quadruple Helix model, Mode 3 innovation analysis, N-tuple helix analysis | knowledge mapping, domain mapping, research landscape visualization |
| Связанные≠ | 4 | 5 |
| Сводка≠ | Quadruple Helix analysis extends the Triple Helix of university-industry-government relations by adding a fourth helix—the media-based and culture-based public, civil society, and users—as a constitutive actor in innovation. It frames innovation as a 'Mode 3' fractal ecosystem in which knowledge is co-produced across multiple spheres, and it situates this within a broader N-tuple generalisation that can add further helices such as the natural environment in the Quintuple Helix. | 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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