手法を比較

	共起語分析	サイエンスマッピング
分野	科学計量学	計量書誌学
系統	Process / pipeline	Process / pipeline
提唱年	1983	2000s
提唱者	Michel Callon, Jean-Pierre Courtial, and colleagues	Katy Börner, Chaomei Chen, and others
種類	Scientometric network analysis technique	Method
原典	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.	Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255.
別名	keyword co-occurrence analysis, co-word mapping, keyword co-word network, CWA	knowledge mapping, domain mapping, research landscape visualization
関連	6	5
概要	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.	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.