Salīdzināt metodes

	Bibliometriskā tematiskās evolūcijas analīze	Analīze pēc līdzvārdiem
Nozare	Zinātnometrija	Zinātnometrija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2017 (bibliometrix package); thematic evolution approach ~2011	1983
Autors	Massimo Aria & Corrado Cuccurullo (bibliometrix package); thematic evolution method from Cobo et al.	Michel Callon, Jean-Pierre Courtial, and colleagues
Tips	Computational scientometric workflow	Scientometric network analysis technique
Pirmavots	Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975.	Callon, M., Courtial, J. P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191–235.
Citi nosaukumi	bibliometrix thematic map analysis, R-based thematic evolution analysis, bibliometrix strategic diagram analysis, thematic evolution analysis with bibliometrix	keyword co-occurrence analysis, co-word mapping, keyword co-word network, CWA
Saistītās	6	6
Kopsavilkums	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.	Co-word analysis is a scientometric technique that quantifies how often pairs of keywords, subject terms, or title words appear together across a corpus of publications. By treating simultaneous occurrence as a proxy for conceptual relatedness, it constructs networks and clusters that reveal the intellectual structure, dominant themes, and emerging sub-fields of a research domain.