השוואת שיטות

	ניתוח סיינטומטרי מבוסס-רשת	ניתוח סיינטומטרי
תחום	סיינטומטריה	סיינטומטריה
משפחה	Process / pipeline	Process / pipeline
שנת המקור	1965 (Price); computational refinement 2000s–2010s	1969 (term); 1963 (Price's foundational work)
הוגה השיטה	Derek J. de Solla Price (network citation structure); Nees Jan van Eck & Ludo Waltman (computational network mapping)	V. V. Nalimov and Z. M. Mulchenko (term coined); Derek J. de Solla Price (foundational methods)
סוג	Quantitative bibliometric method	Quantitative literature analysis
מקור מכונן	van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.	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.
כינויים	scientometric network analysis, bibliometric network analysis, citation network scientometrics, science network mapping	scientometrics, science of science, quantitative science studies, research evaluation analysis
קשורות	6	6
תקציר	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.	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.