Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Analiza Evoluției Tematice Asistată de VOSviewer× | Analiza scientometrică× | |
|---|---|---|
| Domeniu | Scientometrie | Scientometrie |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 2010–2011 | 1969 (term); 1963 (Price's foundational work) |
| Autorul original≠ | Nees Jan van Eck & Ludo Waltman (VOSviewer); thematic evolution methodology associated with Cobo et al. | V. V. Nalimov and Z. M. Mulchenko (term coined); Derek J. de Solla Price (foundational methods) |
| Tip≠ | Scientometric workflow / bibliometric visualization pipeline | Quantitative literature analysis |
| Sursa seminală≠ | van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. 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 ↗ |
| Denumiri alternative | VOSviewer thematic mapping, keyword co-occurrence thematic evolution, science mapping thematic evolution, VOSviewer longitudinal thematic analysis | scientometrics, science of science, quantitative science studies, research evaluation analysis |
| Înrudite | 6 | 6 |
| Rezumat≠ | VOSviewer-assisted thematic evolution analysis is a scientometric pipeline that uses the VOSviewer software to build keyword co-occurrence networks across chronological time slices of a bibliographic dataset, revealing how research themes emerge, converge, fragment, or disappear over time within a scientific field. By coupling VOSviewer's density-based clustering with period-by-period comparison, researchers obtain a visual and quantitative account of a field's intellectual trajectory. | 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. |
| ScholarGateSet de date ↗ |
|
|