Methoden vergleichen

	Multilayer Stochastic Block Model	Multilayer Community Detection
Fachgebiet	Netzwerkanalyse	Netzwerkanalyse
Familie	Machine learning	Machine learning
Entstehungsjahr	2015-2017	2010–2014
Urheber	Peixoto, T. P.; De Bacco, C. and colleagues	Mucha, P. J. et al.; Kivela, M. et al.
Typ	Generative probabilistic model	Community detection algorithm for multilayer networks
Wegweisende Quelle	Peixoto, T. P. (2015). Inferring the mesoscale structure of layered, edge-valued, and time-varying networks. Physical Review E, 92(4), 042807.	Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271.
Aliasnamen	ML-SBM, multilayer SBM, multi-layer stochastic block model, multiplex stochastic block model	multilayer clustering, multiplex community detection, cross-layer community detection, MCD
Verwandt	4	5
Zusammenfassung	The Multilayer Stochastic Block Model (ML-SBM) is a generative probabilistic framework that extends the classical stochastic block model to networks with multiple relation types or layers. It simultaneously infers community structure and block-to-block connection probabilities across all layers, capturing how communities cohere differently depending on context or relationship type.	Multilayer community detection identifies groups of nodes that are densely connected across multiple types of relationships simultaneously. By coupling layers of a network — such as friendship, advice, and collaboration ties — it finds communities that are coherent not just within one relation type but across all of them, revealing structure that single-layer analysis would miss.