Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Аналіз еволюції тем за допомогою бібліометрикс× | Сцієнтометричний аналіз× | |
|---|---|---|
| Галузь | Наукометрія | Наукометрія |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 2017 (bibliometrix package); thematic evolution approach ~2011 | 1969 (term); 1963 (Price's foundational work) |
| Автор методу≠ | Massimo Aria & Corrado Cuccurullo (bibliometrix package); thematic evolution method from Cobo et al. | V. V. Nalimov and Z. M. Mulchenko (term coined); Derek J. de Solla Price (foundational methods) |
| Тип≠ | Computational scientometric workflow | Quantitative literature analysis |
| Основоположне джерело≠ | Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. DOI ↗ | 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 ↗ |
| Інші назви | bibliometrix thematic map analysis, R-based thematic evolution analysis, bibliometrix strategic diagram analysis, thematic evolution analysis with bibliometrix | scientometrics, science of science, quantitative science studies, research evaluation analysis |
| Пов'язані | 6 | 6 |
| Підсумок≠ | Bibliometrix-assisted thematic evolution analysis uses the bibliometrix R package to trace how research themes emerge, mature, decline, or transform across successive time periods within a scientific field. By combining co-word analysis with strategic diagram visualisation, the workflow maps the intellectual structure of a field and reveals longitudinal shifts in topic centrality and development, producing reproducible, publication-ready outputs within a single R environment. | 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. |
| ScholarGateНабір даних ↗ |
|
|