Stochastic Block Model

The Stochastic Block Model (SBM) is a probabilistic model used for network analysis, designed to capture community structures within networks through a matrix of connection probabilities between nodes. This model assumes that network nodes belong to different hidden communities, with varying connection probabilities both within and between communities, thereby enabling effective modeling of complex network structures. Its primary goal is to uncover the underlying modular characteristics of networks, enhancing the accuracy and efficiency of community detection. The SBM has significant applications in social network analysis, bioinformatics, and machine learning, aiding researchers in better understanding the intrinsic patterns and functions of network data.