So sánh phương pháp

	Phân tích Khoa học Dựa trên Mạng	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	1965 (Price); computational refinement 2000s–2010s	1973
Người khởi xướng	Derek J. de Solla Price (network citation structure); Nees Jan van Eck & Ludo Waltman (computational network mapping)	Henry Small
Loại	Quantitative bibliometric method	Method
Công trình gốc	van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.	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	scientometric network analysis, bibliometric network analysis, citation network scientometrics, science network mapping	co-citation mapping, historiograph, direct citation, citation pair analysis
Liên quan	6	5
Tóm tắt	Network-based scientometric analysis applies graph-theoretic methods to bibliographic data — publications, citations, authors, and keywords — to map the intellectual structure of a scientific field. By modeling documents or authors as nodes and their relationships (citations, co-authorships, co-word occurrences) as edges, it reveals clusters of knowledge, central actors, emerging topics, and the flow of ideas across disciplines. Tools such as VOSviewer, Gephi, and the R package bibliometrix are commonly used.	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.