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September 5, 2025Physical review. EOpen Access

Block-corrected modularity for community detection

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Block-corrected modularity uncovers hidden community structures in networks driven by unknown attributes.
The proposed method outperforms traditional null models, especially in synthetic network scenarios.
Efficient spectral methods and Louvain-inspired algorithms maximize modularity for improved community detection.
Analysis demonstrates effectiveness in real-world citation networks using OpenAlex data, correcting for citation patterns.

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This approach reveals community structures driven by unknown attributes, suggesting better analysis of complex networks.

Narimanzadeh et al. (2025) studied this question.

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