Improved Community Detection using Stochastic Block Models

Minhyuk Park; Daniel Wang Feng; Siya Digra; The-Anh Vu-Le; George Chacko; Tandy Warnow

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arXiv · 2408.10464

Improved Community Detection using Stochastic Block Models

Minhyuk Park·Daniel Wang Feng·Siya Digra·The-Anh Vu-Le·George Chacko·Tandy Warnow

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Abstract

Community detection approaches resolve complex networks into smaller groups (communities) that are expected to be relatively edge-dense and well-connected. The stochastic block model (SBM) is one of several approaches used to uncover community structure in graphs. In this study, we demonstrate that SBM software applied to various real-world and synthetic networks produces poorly-connected to disconnected clusters. We present simple modifications to improve the connectivity of SBM clusters, and show that the modifications improve accuracy using simulated networks.

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Minhyuk Park, Daniel Wang Feng, Siya Digra, The-Anh Vu-Le, George Chacko, Tandy Warnow. 2024-08-20. Improved Community Detection using Stochastic Block Models. https://arxiv.org/abs/2408.10464

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