方法对比

	文献计量分析	共词分析	范围界定审查
领域	科学计量学	科学计量学	科学计量学
方法族	Process / pipeline	Process / pipeline	Process / pipeline
起源年份	1969 (term coined); practice dates to 1920s–1930s	1983	2005
提出者	Alan Pritchard (coined term); earlier quantitative work by Paul Otlet (1934) and S. C. Bradford (1934)	Michel Callon, Jean-Pierre Courtial, and colleagues	Hilary Arksey & Lisa O'Malley
类型	Quantitative literature analysis	Scientometric network analysis technique	Evidence synthesis review design
开创性文献	Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348–349.	Callon, M., Courtial, J. P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191–235.	Arksey, H., & O'Malley, L. (2005). Scoping studies: towards a methodological framework. International Journal of Social Research Methodology, 8(1), 19–32.
别名	bibliometrics, bibliometric study, bibliometric mapping, publication analysis	keyword co-occurrence analysis, co-word mapping, keyword co-word network, CWA	scoping study, literature scoping, evidence mapping review, rapid evidence map
相关	6	6	6
摘要	Bibliometric analysis applies statistical and mathematical methods to bibliographic records — publications, citations, authors, journals, and keywords — to measure and map the structure, output, and intellectual evolution of a research field. It is widely used to identify influential works, prolific authors, productive journals, collaboration networks, and emerging research themes across any academic discipline.	Co-word analysis is a scientometric technique that quantifies how often pairs of keywords, subject terms, or title words appear together across a corpus of publications. By treating simultaneous occurrence as a proxy for conceptual relatedness, it constructs networks and clusters that reveal the intellectual structure, dominant themes, and emerging sub-fields of a research domain.	A scoping review is a systematic evidence-synthesis method that maps the breadth and nature of research on a topic — identifying key concepts, evidence types, and gaps — without necessarily appraising study quality or pooling effect sizes. Developed by Arksey and O'Malley (2005) and refined by Levac and colleagues (2010), it is particularly valuable for emerging or heterogeneous fields where a full systematic review would be premature or infeasible.