Improved Community Detection using Stochastic Block Models
<|reference_start|>Improved Community Detection using Stochastic Block Models: 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.<|reference_end|>
@article{park2024improved,
    title={Improved Community Detection using Stochastic Block Models},
    author={Minhyuk Park and Daniel Wang Feng and Siya Digra and The-Anh Vu-Le and
  George Chacko and Tandy Warnow},
    journal={arXiv preprint arXiv:2408.10464},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.10464},
    primaryClass={cs.SI}
}