Sammenlign metoder

	Bibliometrisk kartlegging med bibliometrix	Vitenskapskartlegging
Fagfelt	Scientometri	Bibliometri
Familie	Process / pipeline	Process / pipeline
Opprinnelsesår	2017	2000s
Opphavsperson	Massimo Aria & Corrado Cuccurullo (bibliometrix R package)	Katy Börner, Chaomei Chen, and others
Type	Computational bibliometric pipeline	Method
Opprinnelig kilde	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 science mapping, R-based science mapping, bibliometrix bibliometric mapping, bibliometrix-driven knowledge mapping	knowledge mapping, domain mapping, research landscape visualization
Relaterte	6	5
Sammendrag	bibliometrix-assisted science mapping is a computational approach that uses the bibliometrix R package to retrieve, clean, and analyze large bibliographic datasets, producing structured visual maps of how knowledge in a field is organized, interconnected, and evolving over time. It combines descriptive bibliometrics with network analysis and strategic clustering techniques to reveal intellectual structure, thematic frontiers, and influential actors in 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.