So sánh phương pháp

	Phân tích đồng trích dẫn dựa trên mạng lưới	Phân tích đồng trích dẫn (Co-Citation Analysis)
Lĩnh vực	Trắc lượng khoa học	Trắc lượng thư mục
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1973 (co-citation); network-analytic extension widely adopted 2000s–2010s	1973
Người khởi xướng	Henry Small (co-citation foundation); network visualization extended by Chaomei Chen and others	Henry Small
Loại	Bibliometric network analysis	Method
Công trình gốc	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.	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	co-citation network analysis, bibliometric network co-citation, co-citation mapping, CCA network approach	co-citation mapping, historiograph, direct citation, citation pair analysis
Liên quan	6	5
Tóm tắt	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.	Co-citation analysis is a method that identifies the intellectual structure of a research domain by examining how frequently pairs of documents are cited together in other publications. When two papers are frequently cited together in the literature, they are considered co-cited, indicating they are conceptually related or influential within the same research community. Developed by Henry Small in 1973, co-citation analysis maps the 'invisible colleges' of science—networks of researchers working on related problems—and reveals how knowledge domains evolve over time.