Porovnať metódy

	Analýza spoločnej citovanosti časopisov	Mapovanie vedy
Odbor	Bibliometria	Bibliometria
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	1981	2000s
Tvorca	Henry Small, Henry White, and others	Katy Börner, Chaomei Chen, and others
Typ	Method	Method
Pôvodný zdroj	White, H. D., & Griffith, B. C. (1981). Author co-citation: A literature measure of intellectual structure. Journal of the American Society for Information Science, 32(3), 163–171.	Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255.
Ďalšie názvy	journal citation mapping, journal network analysis, cited source co-citation	knowledge mapping, domain mapping, research landscape visualization
Príbuzné	4	5
Zhrnutie	Journal co-citation analysis is a bibliometric method that maps the intellectual structure of a research field by analyzing how frequently pairs of journals are cited together in the same papers. Two journals are co-cited when papers cite both journals, indicating that the journals are perceived as intellectually related by the citing authors. This extension of paper-level co-citation analysis to the journal level reveals the topological structure of journal relationships, disciplinary boundaries, and the role of different journals within research communities.	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.