手法を比較

	時間スライス計量書誌分析	テーマ進化分析
分野	科学計量学	科学計量学
系統	Process / pipeline	Process / pipeline
提唱年	1980s–1990s	2011
提唱者	Derived from scientometrics tradition; temporal slicing formalized in longitudinal bibliometric studies from the 1980s onward	Manuel J. Cobo and colleagues (University of Granada)
種類	Quantitative longitudinal analysis	Quantitative bibliometric technique
原典	Small, H. (1999). Visualizing science by citation mapping. Journal of the American Society for Information Science, 50(9), 799-813.	Cobo, M. J., Lopez-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.
別名	temporal scientometrics, period-based scientometric analysis, time-window scientometrics, longitudinal scientometric analysis	TEA, thematic development analysis, temporal thematic mapping, longitudinal theme analysis
関連	6	6
概要	Time-sliced scientometric analysis divides a bibliographic corpus into discrete temporal windows — commonly five- or ten-year periods — and applies standard scientometric indicators (publication counts, citation rates, h-index, collaboration networks, keyword co-occurrence) within each slice. By comparing results across slices, researchers can reconstruct how a scientific field has grown, shifted focus, formed new collaborations, or declined in influence over time. The approach combines the rigor of quantitative scientometrics with an explicit longitudinal dimension.	Thematic evolution analysis is a bibliometric technique that divides a body of literature into consecutive time periods and tracks how research themes emerge, consolidate, split, merge, or disappear across those periods. By combining co-word analysis, clustering, and strategic diagrams for each time slice, it produces a dynamic picture of a field's intellectual development rather than a static snapshot.