手法を比較

	書誌計量学的法則：ロットカの法則、ブラッドフォードの法則、ジップの法則	共引用分析	サイエンスマッピング
分野	計量書誌学	計量書誌学	計量書誌学
系統	Process / pipeline	Process / pipeline	Process / pipeline
提唱年	1926–1949	1973	2000s
提唱者	Alfred J. Lotka, Samuel C. Bradford, George K. Zipf	Henry Small	Katy Börner, Chaomei Chen, and others
種類	Concept	Method	Method
原典	Lotka, A. J. (1926). The frequency distribution of scientific productivity. Journal of the Washington Academy of Sciences, 16(12), 317–323.	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.
別名	bibliometric distributions, productivity laws, frequency laws, information science laws	co-citation mapping, historiograph, direct citation, citation pair analysis	knowledge mapping, domain mapping, research landscape visualization
関連	3	5	5
概要	Three foundational empirical laws describe the structure and distribution of scientific information: Lotka's Law characterizes author productivity (most authors publish few papers; a few publish many), Bradford's Law describes journal concentration (a small number of core journals contain the majority of papers on a topic), and Zipf's Law models word and term frequency (word frequency inversely proportional to its rank). These regularities, discovered in the mid-20th century, are remarkably robust across disciplines and have become essential tools for understanding research productivity, organizing information resources, and designing search strategies.	Co-citation analysis is a method that identifies the intellectual structure of a research domain by examining how frequently pairs of documents are cited together in other publications. When two papers are frequently cited together in the literature, they are considered co-cited, indicating they are conceptually related or influential within the same research community. Developed by Henry Small in 1973, co-citation analysis maps the 'invisible colleges' of science—networks of researchers working on related problems—and reveals how knowledge domains evolve over time.	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.