手法を比較

	書誌計量学支援システマティック・レビュー	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	2017	2000s
提唱者	Massimo Aria & Corrado Cuccurullo (bibliometrix R package)	Katy Börner, Chaomei Chen, and others
種類	Software-assisted systematic review	Method
原典	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.
別名	bibliometrix SLR, R-bibliometrix systematic review, bibliometrix-based literature review, bibliometrix-enhanced SLR	knowledge mapping, domain mapping, research landscape visualization
関連	6	5
概要	A bibliometrix-assisted systematic literature review integrates the R package bibliometrix — developed by Aria and Cuccurullo (2017) — into the standard systematic review pipeline to automate and visualize bibliometric performance and science-mapping analyses. It combines the transparency and reproducibility of a protocol-driven systematic search with quantitative tools for tracking publication trends, author collaboration networks, keyword co-occurrence, and thematic evolution across a 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.