So sánh phương pháp

	Phân tích đồng trích dẫn dựa trên mạng lưới	Phân tích khoa học liệu
Lĩnh vực	Trắc lượng khoa học	Trắc lượng khoa học
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1973 (co-citation); network-analytic extension widely adopted 2000s–2010s	1969 (term); 1963 (Price's foundational work)
Người khởi xướng	Henry Small (co-citation foundation); network visualization extended by Chaomei Chen and others	V. V. Nalimov and Z. M. Mulchenko (term coined); Derek J. de Solla Price (foundational methods)
Loại	Bibliometric network analysis	Quantitative literature analysis
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.	Nalimov, V. V., & Mulchenko, Z. M. (1969). Naukometriya: Izucheniye razvitiya nauki kak informatsionnogo protsessa [Scientometrics: The Study of the Development of Science as an Information Process]. Nauka.
Tên gọi khác	co-citation network analysis, bibliometric network co-citation, co-citation mapping, CCA network approach	scientometrics, science of science, quantitative science studies, research evaluation analysis
Liên quan	6	6
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.	Scientometric analysis applies statistical and computational methods to publication and citation data to measure the growth, structure, and impact of scientific fields. Drawing on databases such as Web of Science, Scopus, or OpenAlex, it quantifies output trends, identifies leading authors and institutions, maps intellectual networks, and evaluates research impact — transforming large bibliographic corpora into evidence-based portraits of how knowledge develops and spreads.