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arXiv · 2406.17556

Modularity Based Community Detection in Hypergraphs

Bogumił Kamiński·Paweł Misiorek·Paweł Prałat·François Théberge
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Abstract

In this paper, we propose a scalable community detection algorithm using hypergraph modularity function, h-Louvain. It is an adaptation of the classical Louvain algorithm in the context of hypergraphs. We observe that a direct application of the Louvain algorithm to optimize the hypergraph modularity function often fails to find meaningful communities. We propose a solution to this issue by adjusting the initial stage of the algorithm via carefully and dynamically tuned linear combination of the graph modularity function of the corresponding two-section graph and the desired hypergraph modularity function. The process is guided by Bayesian optimization of the hyper-parameters of the proposed procedure. Various experiments on synthetic as well as real-world networks are performed showing that this process yields improved results in various regimes.

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Bogumił Kamiński, Paweł Misiorek, Paweł Prałat, François Théberge. 2024-06-25. Modularity Based Community Detection in Hypergraphs. https://arxiv.org/abs/2406.17556

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