So sánh phương pháp

	Phân tích đồng trích dẫn có hỗ trợ bibliometrix	Phân tích đồng trích dẫn dựa trên mạng lưới
Lĩnh vực	Trắc lượng khoa học	Trắc lượng khoa học
Họ	Process / pipeline	Process / pipeline
Năm ra đời	2017 (bibliometrix implementation); 1973 (co-citation concept)	1973 (co-citation); network-analytic extension widely adopted 2000s–2010s
Người khởi xướng	Co-citation: Henry Small (1973); bibliometrix package: Massimo Aria & Corrado Cuccurullo (2017)	Henry Small (co-citation foundation); network visualization extended by Chaomei Chen and others
Loại	Computational scientometric pipeline	Bibliometric network analysis
Công trình gốc	Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975.	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.
Tên gọi khác	R bibliometrix co-citation, bibliometrix CCA, co-citation network analysis with bibliometrix, bibliometrix cocitation mapping	co-citation network analysis, bibliometric network co-citation, co-citation mapping, CCA network approach
Liên quan	6	6
Tóm tắt	bibliometrix-assisted co-citation analysis combines Henry Small's co-citation measure with the open-source R package bibliometrix to map the intellectual structure of a research field. When two documents are frequently cited together by third papers, they are considered intellectually linked; the bibliometrix package automates construction of the co-citation matrix, similarity normalization, community detection, and network visualization, turning raw bibliographic exports into interpretable science maps.	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.