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Author Bibliographic Coupling Analysis×Author-Keyword Co-Occurrence Mapping×
분야계량서지학계량서지학
계열Process / pipelineProcess / pipeline
기원 연도20081983
창시자Dangzhi Zhao & Andreas StrotmannMichel Callon, Jean-Pierre Courtial, William Turner & Serge Bauin; later Ying Ding, Gobinda Chowdhury & Schubert Foo
유형Science-mapping pipeline coupling authors by shared referencesKeyword co-occurrence network mapping pipeline
원전Zhao, D., & Strotmann, A. (2008). Evolution of research activities and intellectual influences in information science 1996-2005: Introducing author bibliographic-coupling analysis. Journal of the American Society for Information Science and Technology, 59(13), 2070-2086. DOI ↗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. DOI ↗
별칭ABCA, Author-Level Bibliographic Coupling, Coupling of Authors by Shared ReferencesAuthor Keyword Network Mapping, Keyword Co-Occurrence Analysis, Conceptual Structure Mapping
관련33
요약Author bibliographic coupling analysis (ABCA) maps the current intellectual structure of a field by linking authors through the references they share. Introduced by Dangzhi Zhao and Andreas Strotmann in 2008, the method extends classic bibliographic coupling — which couples two documents when they cite the same earlier work — up to the level of authors: two authors are coupled to the degree that their bodies of work draw on the same references. Because coupling is fixed at the moment of publication and reflects what authors are reading and building on right now, ABCA captures the active research front and the intellectual affinities among currently productive authors, complementing author co-citation analysis, which instead reflects a field's slowly accumulating, more retrospective base of cited authorities.Author-keyword co-occurrence mapping reveals the conceptual structure of a research field by analyzing the keywords authors attach to their papers. It is a form of co-word analysis, the technique Michel Callon and colleagues introduced in 1983 to study how scientific problems are constructed through the language of the literature. The premise is that keywords appearing together in the same documents are conceptually linked, so counting these co-occurrences across a corpus and normalizing them into association strengths yields a network in which terms cluster into coherent themes. Ying Ding, Gobinda Chowdhury, and Schubert Foo's 2001 study mapped information-retrieval research with exactly this approach, demonstrating its value for charting a field's topics. The method offers a content-based complement to citation-based maps, showing what a field is about rather than which works it cites.
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