방법 비교

	시간 분할 계량정보 분석	주제 진화 분석
분야	과학계량학	과학계량학
계열	Process / pipeline	Process / pipeline
기원 연도	1980s–1990s	2011
창시자	Derived from scientometrics tradition; temporal slicing formalized in longitudinal bibliometric studies from the 1980s onward	Manuel J. Cobo and colleagues (University of Granada)
유형	Quantitative longitudinal analysis	Quantitative bibliometric technique
원전	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.
별칭	temporal scientometrics, period-based scientometric analysis, time-window scientometrics, longitudinal scientometric analysis	TEA, thematic development analysis, temporal thematic mapping, longitudinal theme analysis
관련	6	6
요약	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.