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	Blockmodeling	Analisi delle Reti Sociali	Triad Census
Campo	Sociology	Analisi delle reti	Sociology
Famiglia	Process / pipeline	Machine learning	Process / pipeline
Anno di origine	1976	1934 (sociometry); 1994 (modern formalization)	1970
Ideatore	Harrison White, Scott Boorman & Ronald Breiger	Moreno, J.L.; formalized by Wasserman & Faust	Paul Holland & Samuel Leinhardt
Tipo	Network partitioning into positions and a reduced role structure	Structural/relational analysis framework	Enumeration of the 16 isomorphism classes of directed triads
Fonte seminale	White, H. C., Boorman, S. A., & Breiger, R. L. (1976). Social structure from multiple networks. I. Blockmodels of roles and positions. American Journal of Sociology, 81(4), 730–780.	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1	Holland, P. W., & Leinhardt, S. (1970). A method for detecting structure in sociometric data. American Journal of Sociology, 76(3), 492–513.
Alias	block modeling, blockmodel analysis, generalized blockmodeling, CONCOR	SNA, network analysis, sociometric analysis, relational analysis	triad count, triadic census, 16-type triad census, MAN triad census
Correlati	4	5	4
Sintesi	Blockmodeling is a family of methods that simplify a social network by partitioning its actors into positions — groups of actors who are equivalent in their pattern of ties — and summarizing the relations between positions as a compact image, or reduced role structure. Introduced by Harrison White, Scott Boorman, and Ronald Breiger in 1976, it shifts attention from individuals to the structural roles they occupy.	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.	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.