방법 비교

	Relative Specialization / Activity Index	Collaboration Distance and Erdős Number Analysis
분야	계량서지학	계량서지학
계열	Process / pipeline	Process / pipeline
기원 연도	1986	2001
창시자	J. Davidson Frame (activity index); András Schubert & Tibor Braun (relative indicators)	M. E. J. Newman (collaboration networks); Rodrigo de Castro & Jerrold Grossman (Erdős number)
유형	Normalized bibliometric indicator of revealed research specialization	Network-distance pipeline over co-authorship graphs
원전	Schubert, A., & Braun, T. (1986). Relative indicators and relational charts for comparative assessment of publication output and citation impact. Scientometrics, 9(5-6), 281-291.	Newman, M. E. J. (2001). The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences, 98(2), 404-409.
별칭	Activity Index, Relative Specialization Index, Revealed Comparative Advantage in Science, Attractivity Index	Erdős Number Analysis, Co-Authorship Distance, Collaboration Geodesic Analysis, Scientific Small-World Analysis
관련	3	3
요약	The Relative Specialization Index and the closely related Activity Index measure how much a country, institution, or other unit concentrates its research effort in a given field relative to a global benchmark. The Activity Index, popularized by J. Davidson Frame in the 1970s, compares a unit's share of its own output devoted to a field against the world's share of output in that field: a value above 1 means the unit is more active (more specialized) in that field than the world average, and below 1 means less. András Schubert and Tibor Braun's relative-indicator framework formalized this family and introduced bounded, symmetric variants and 'relational charts' that pair publication activity with citation 'attractivity'. These indices are the scientometric analogue of revealed comparative advantage in trade and are central to national and institutional research-profiling.	Collaboration distance analysis measures how closely connected scientists are through chains of co-authorship. Two researchers who have written a paper together are at distance 1; if they share a co-author but never wrote together, distance 2; and so on. The most famous instance is the Erdős number, the collaboration distance to the prolific mathematician Paul Erdős, popularized by the Erdős Number Project and analyzed by Rodrigo de Castro and Jerrold Grossman. M. E. J. Newman's landmark 2001 PNAS study generalized this idea, constructing large co-authorship networks across physics, biomedicine, and computer science and showing that they are 'small worlds': despite millions of authors, typical shortest paths are short and local clustering is high. Collaboration distance analysis thus characterizes the connectivity and reach of scientific communities through the geometry of their co-authorship graphs.