방법 비교

	사회 연결망 분석	Structural Equivalence	Triad Census
분야	네트워크 분석	Sociology	Sociology
계열	Machine learning	Process / pipeline	Process / pipeline
기원 연도	1934 (sociometry); 1994 (modern formalization)	1971	1970
창시자	Moreno, J.L.; formalized by Wasserman & Faust	François Lorrain & Harrison White	Paul Holland & Samuel Leinhardt
유형	Structural/relational analysis framework	Equivalence relation grouping actors with identical tie patterns	Enumeration of the 16 isomorphism classes of directed triads
원전	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1	Lorrain, F., & White, H. C. (1971). Structural equivalence of individuals in social networks. The Journal of Mathematical Sociology, 1(1), 49–80.	Holland, P. W., & Leinhardt, S. (1970). A method for detecting structure in sociometric data. American Journal of Sociology, 76(3), 492–513.
별칭	SNA, network analysis, sociometric analysis, relational analysis	structural equivalence analysis, positional equivalence, Euclidean equivalence of actors, equivalence classes	triad count, triadic census, 16-type triad census, MAN triad census
관련	5	5	4
요약	Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system.	Structural equivalence identifies actors who occupy the same position in a network because they have identical ties to identical others. Defined by François Lorrain and Harrison White in 1971, it formalizes the idea that two people are interchangeable in the social structure when they relate to exactly the same set of third parties, and it provides the foundation for partitioning networks into positions and building blockmodels.	The triad census counts how many of a directed network's three-actor subgroups fall into each of the 16 possible types of triad, providing a compact fingerprint of the network's local structure. Introduced by Paul Holland and Samuel Leinhardt in 1970, it is the standard way to test structural theories — balance, clustering, transitivity, ranked clusters — by comparing the observed distribution of triad types against what a random network would produce.