Salīdzināt metodes

	Laika griezumos sadalīta tematiskās evolūcijas analīze	Analīze pēc līdzvārdiem
Nozare	Zinātnometrija	Zinātnometrija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2011–2012	1983
Autors	Cobo, López-Herrera, Herrera-Viedma & Herrera	Michel Callon, Jean-Pierre Courtial, and colleagues
Tips	Longitudinal bibliometric analysis	Scientometric network analysis technique
Pirmavots	Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382–1402.	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	longitudinal thematic mapping, temporal thematic evolution, time-period thematic analysis, diachronic science mapping	keyword co-occurrence analysis, co-word mapping, keyword co-word network, CWA
Saistītās	6	6
Kopsavilkums	Time-sliced thematic evolution analysis is a bibliometric method that divides a corpus of publications into consecutive time windows and tracks how research themes emerge, consolidate, split, merge, or disappear across those periods. By applying co-word analysis and strategic-diagram mapping within each slice and then linking themes across slices, it reveals the intellectual trajectory of a research field over time.	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.