Compare methods

	Author Bibliographic Coupling Analysis	Direct Citation Clustering of Science
Field	Bibliometrics	Bibliometrics
Family	Process / pipeline	Process / pipeline
Year of origin	2008	2010
Originator	Dangzhi Zhao & Andreas Strotmann	Kevin W. Boyack & Richard Klavans; Ludo Waltman & Nees Jan van Eck
Type	Science-mapping pipeline coupling authors by shared references	Large-scale publication-level network clustering pipeline
Seminal source	Zhao, 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.	Boyack, K. W., & Klavans, R. (2010). Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? Journal of the American Society for Information Science and Technology, 61(12), 2389-2404.
Aliases	ABCA, Author-Level Bibliographic Coupling, Coupling of Authors by Shared References	Direct Citation Network Clustering, Publication-Level Citation Clustering, Citation-Based Science Mapping
Related	3	3
Summary	Author 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.	Direct citation clustering maps the structure of science by linking publications through the citations that run directly between them and partitioning the resulting network into research areas. Unlike co-citation (which links papers cited together) or bibliographic coupling (which links papers sharing references), direct citation uses the citation itself as the edge: paper A is connected to paper B because A cites B. Kevin Boyack and Richard Klavans's 2010 comparison of citation approaches found that, at scale, direct citation can represent the research front at least as accurately as the alternatives, and Ludo Waltman and Nees Jan van Eck's 2012 methodology showed how to cluster very large direct-citation networks — millions of publications — into a coherent, publication-level classification of science using modularity-based community detection. Together these works established direct citation clustering as a leading technique for building large-scale science maps.