Сравнение методов

	Сетевой анализ совместных цитирований	Картографирование науки (Science Mapping)
Область	Наукометрия	Библиометрия
Семейство	Process / pipeline	Process / pipeline
Год появления	1973 (co-citation); network-analytic extension widely adopted 2000s–2010s	2000s
Автор метода	Henry Small (co-citation foundation); network visualization extended by Chaomei Chen and others	Katy Börner, Chaomei Chen, and others
Тип	Bibliometric network analysis	Method
Основополагающий источник	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.	Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255.
Другие названия	co-citation network analysis, bibliometric network co-citation, co-citation mapping, CCA network approach	knowledge mapping, domain mapping, research landscape visualization
Связанные	6	5
Сводка	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.	Science mapping is a bibliometric visualization method that creates visual representations of research domains, showing the structure, development, and relationships of scientific fields. Using bibliographic data (citations, keywords, authors, journals), science mapping algorithms generate network diagrams where nodes represent documents, concepts, or authors and edges represent relationships (citation, collaboration, semantic similarity). The resulting maps make invisible intellectual structures visible, enabling researchers to understand field topology, identify emerging areas, and navigate disciplinary landscapes. Pioneered by Börner, Chen, and Boyack in the 2000s, science mapping has become a standard tool in research evaluation and strategic planning.