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arXiv · 2502.03662

EC-SBM Synthetic Network Generator

The-Anh Vu-Le·Lahari Anne·George Chacko·Tandy Warnow
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Abstract

Generating high-quality synthetic networks with realistic community structure is vital to effectively evaluate community detection algorithms. In this study, we propose a new synthetic network generator called the Edge-Connected Stochastic Block Model (EC-SBM). The goal of EC-SBM is to take a given clustered real-world network and produce a synthetic network that resembles the clustered real-world network with respect to both network and community-specific criteria. In particular, we focus on simulating the internal edge connectivity of the clusters in the reference clustered network. Our extensive performance study on large real-world networks shows that EC-SBM has high accuracy in both network and community-specific criteria, and is generally more accurate than current alternative approaches for this problem. Furthermore, EC-SBM is fast enough to scale to real-world networks with millions of nodes.

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The-Anh Vu-Le, Lahari Anne, George Chacko, Tandy Warnow. 2025-02-05. EC-SBM Synthetic Network Generator. https://doi.org/10.1007/s41109-025-00701-2

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