Сравнение на методи

	Мрежов анализ на ко-цитиранията	Наукометричен анализ
Област	Наукометрия	Наукометрия
Семейство	Process / pipeline	Process / pipeline
Година на възникване	1973 (co-citation); network-analytic extension widely adopted 2000s–2010s	1969 (term); 1963 (Price's foundational work)
Създател	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)
Тип	Bibliometric network analysis	Quantitative literature analysis
Основополагащ източник	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.
Други названия	co-citation network analysis, bibliometric network co-citation, co-citation mapping, CCA network approach	scientometrics, science of science, quantitative science studies, research evaluation analysis
Свързани	6	6
Резюме	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.