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공동 저술 네트워크 분석×과학 지도 제작×
분야계량서지학계량서지학
계열Process / pipelineProcess / pipeline
기원 연도20012000s
창시자Mark E. J. Newman and othersKaty Börner, Chaomei Chen, and others
유형MethodMethod
원전Newman, M. E. J. (2001). The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences, 98(2), 404–409. DOI ↗Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255. DOI ↗
별칭collaboration network, authorship network, research collaboration mappingknowledge mapping, domain mapping, research landscape visualization
관련45
요약Co-authorship network analysis is a method that maps research collaboration patterns by treating authors as nodes and co-authored papers as edges in a network graph. The structure, density, and centrality patterns of this network reveal how researchers connect, collaborate across institutions and disciplines, and form research communities. Pioneered formally by Newman (2001), co-authorship analysis provides quantitative insights into the social fabric of science, revealing collaboration patterns, identifying scientific leaders, and detecting institutional or disciplinary boundaries.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.
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