方法对比

	主题演化分析	科学制图
领域	科学计量学	文献计量学
方法族	Process / pipeline	Process / pipeline
起源年份	2011	2000s
提出者	Manuel J. Cobo and colleagues (University of Granada)	Katy Börner, Chaomei Chen, and others
类型	Quantitative bibliometric technique	Method
开创性文献	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.	Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255.
别名	TEA, thematic development analysis, temporal thematic mapping, longitudinal theme analysis	knowledge mapping, domain mapping, research landscape visualization
相关	6	5
摘要	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.	Science mapping is a bibliometric visualization method that creates visual representations of research domains, showing the structure, development, and relationships of scientific fields. Using bibliographic data (citations, keywords, authors, journals), science mapping algorithms generate network diagrams where nodes represent documents, concepts, or authors and edges represent relationships (citation, collaboration, semantic similarity). The resulting maps make invisible intellectual structures visible, enabling researchers to understand field topology, identify emerging areas, and navigate disciplinary landscapes. Pioneered by Börner, Chen, and Boyack in the 2000s, science mapping has become a standard tool in research evaluation and strategic planning.