Порівняння методів

	Generalized Blockmodeling	Аналіз соціальних мереж
Галузь	Sociology	Мережевий аналіз
Родина	Process / pipeline	Machine learning
Рік появи	2005	1934 (sociometry); 1994 (modern formalization)
Автор методу	Patrick Doreian, Vladimir Batagelj & Anuška Ferligoj	Moreno, J.L.; formalized by Wasserman & Faust
Тип	Direct optimization partition of a network into positions with typed blocks	Structural/relational analysis framework
Основоположне джерело	Doreian, P., Batagelj, V., & Ferligoj, A. (2005). Generalized Blockmodeling. Cambridge University Press. ISBN: 978-0-521-84085-9	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1
Інші назви	generalized blockmodel, direct blockmodeling, pre-specified blockmodeling, Doreian-Batagelj-Ferligoj blockmodeling	SNA, network analysis, sociometric analysis, relational analysis
Пов'язані	5	5
Підсумок	Generalized blockmodeling, developed by Doreian, Batagelj, and Ferligoj, partitions the actors of a network into positions and simultaneously characterizes the ties between positions as one of several allowed block types — null, complete, regular, dominant, and others. Rather than the indirect, two-step approach of computing equivalences and then clustering, it directly searches for the partition that minimizes the inconsistency between the observed network and an idealized block structure, optionally one the analyst pre-specifies from theory.	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.