Сравнение методов

	Анализ сетей типа «малый мир» и безмасштабных сетей	Стохастическая блочная модель
Область	Сетевой анализ	Сетевой анализ
Семейство	Process / pipeline	Process / pipeline
Год появления	1998 (small-world); 1999 (scale-free)	1983
Автор метода	—	—
Тип	Descriptive / exploratory network analysis	Probabilistic generative graph model
Основополагающий источник	Watts, D.J. & Strogatz, S.H. (1998). Collective Dynamics of 'Small-World' Networks. Nature, 393(6684), 440-442.	Holland, P.W., Laskey, K.B. & Leinhardt, S. (1983). Stochastic Blockmodels: First Steps. Social Networks, 5(2), 109-137.
Другие названия	Küçük Dünya ve Ölçek-Bağımsız Ağ Analizi, small-world network, scale-free network, preferential attachment analysis	SBM, degree-corrected SBM, DCSBM, Stokastik Blok Modeli (SBM)
Связанные	9	7
Сводка	Small-world and scale-free network analysis tests whether a real-world network exhibits two landmark topological signatures identified in 1998-1999: the Watts-Strogatz small-world property (high local clustering combined with short average path lengths) and the Barabási-Albert scale-free property (a degree distribution that follows a power law, meaning a small number of hubs connect to a disproportionately large share of other nodes). Together these frameworks transformed network science by showing that many social, biological, and technological networks share a common structural grammar.	The Stochastic Block Model (SBM), introduced by Holland, Laskey and Leinhardt (1983), is a probabilistic generative model for graphs that assigns nodes to latent blocks and parametrically estimates the connection probabilities between blocks. It is the foundational approach for community detection, core-periphery identification, and hierarchical structure discovery in network analysis.