Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Сцієнтометричний аналіз× | Картографування науки× | |
|---|---|---|
| Галузь≠ | Наукометрія | Бібліометрія |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1969 (term); 1963 (Price's foundational work) | 2000s |
| Автор методу≠ | V. V. Nalimov and Z. M. Mulchenko (term coined); Derek J. de Solla Price (foundational methods) | Katy Börner, Chaomei Chen, and others |
| Тип≠ | Quantitative literature analysis | Method |
| Основоположне джерело≠ | Nalimov, V. V., & Mulchenko, Z. M. (1969). Naukometriya: Izucheniye razvitiya nauki kak informatsionnogo protsessa [Scientometrics: The Study of the Development of Science as an Information Process]. Nauka. link ↗ | Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255. DOI ↗ |
| Інші назви≠ | scientometrics, science of science, quantitative science studies, research evaluation analysis | knowledge mapping, domain mapping, research landscape visualization |
| Пов'язані≠ | 6 | 5 |
| Підсумок≠ | Scientometric analysis applies statistical and computational methods to publication and citation data to measure the growth, structure, and impact of scientific fields. Drawing on databases such as Web of Science, Scopus, or OpenAlex, it quantifies output trends, identifies leading authors and institutions, maps intellectual networks, and evaluates research impact — transforming large bibliographic corpora into evidence-based portraits of how knowledge develops and spreads. | 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. |
| ScholarGateНабір даних ↗ |
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