方法对比

	Main Path Analysis	Direct Citation Clustering of Science
领域	文献计量学	文献计量学
方法族	Process / pipeline	Process / pipeline
起源年份	1989	2010
提出者	Norman P. Hummon & Patrick Doreian	Kevin W. Boyack & Richard Klavans; Ludo Waltman & Nees Jan van Eck
类型	Citation-network traversal pipeline for knowledge trajectories	Large-scale publication-level network clustering pipeline
开创性文献	Hummon, N. P., & Doreian, P. (1989). Connectivity in a citation network: The development of DNA theory. Social Networks, 11(1), 39-63.	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.
别名	MPA, Citation Main Path Analysis, Knowledge Flow Path Analysis	Direct Citation Network Clustering, Publication-Level Citation Clustering, Citation-Based Science Mapping
相关	3	3
摘要	Main path analysis (MPA) traces the principal trajectory of knowledge development through a citation network. Introduced by Norman Hummon and Patrick Doreian in their 1989 study of the discovery of DNA, the method treats a field's literature as a directed acyclic graph in which documents point backward in time to the work they cite. Rather than mapping the whole network, MPA weights each citation link by how central it is to the flow of ideas — how many knowledge-carrying paths run through it — and then extracts the chain of most-traversed links from the field's earliest sources to its most recent sinks. The result is a compact 'main path': an ordered sequence of papers that represents the backbone along which a research front actually developed.	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.