Comparer des méthodes

	Analyse de co-citation basée sur les réseaux	Cartographie scientifique
Domaine	Scientométrie	Bibliométrie
Famille	Process / pipeline	Process / pipeline
Année d'origine	1973 (co-citation); network-analytic extension widely adopted 2000s–2010s	2000s
Auteur d'origine	Henry Small (co-citation foundation); network visualization extended by Chaomei Chen and others	Katy Börner, Chaomei Chen, and others
Type	Bibliometric network analysis	Method
Source fondatrice	Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265–269.	Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255.
Alias	co-citation network analysis, bibliometric network co-citation, co-citation mapping, CCA network approach	knowledge mapping, domain mapping, research landscape visualization
Apparentées	6	5
Résumé	Network-based co-citation analysis is a bibliometric technique that measures how often pairs of documents are cited together by later works, then models those relationships as a weighted network. Nodes represent documents (or authors or journals), edges represent co-citation frequency, and network algorithms identify clusters of intellectually related literature. It is widely used in systematic and scoping reviews to map the intellectual structure of a research field.	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.