Comparer des méthodes

	couplage bibliographique assisté par bibliometrix	Cartographie scientifique
Domaine	Scientométrie	Bibliométrie
Famille	Process / pipeline	Process / pipeline
Année d'origine	Base method 1963; R-package workflow 2017	2000s
Auteur d'origine	Bibliographic coupling: M. M. Kessler (1963); bibliometrix package: Aria & Cuccurullo (2017)	Katy Börner, Chaomei Chen, and others
Type	Quantitative scientometric network analysis	Method
Source fondatrice	Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975.	Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255.
Alias	bibliometrix bibliographic coupling, R-based bibliographic coupling, coupling analysis via bibliometrix, biblioNetwork coupling	knowledge mapping, domain mapping, research landscape visualization
Apparentées	5	5
Résumé	Bibliometrix-assisted bibliographic coupling applies the open-source R package bibliometrix to construct and analyse bibliographic coupling networks, in which two documents are linked by the number of references they share. The workflow automates record import, network construction, community detection, and summary statistics within a single reproducible R environment, making it accessible to researchers without dedicated scientometric software licences.	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.