Lower Ricci Curvature for Efficient Community Detection
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Abstract (arXiv)
This study introduces the Lower Ricci Curvature (LRC), a novel, scalable, and scale-free discrete curvature designed to enhance community detection in networks. Addressing the computational challenges posed by existing curvature-based methods, LRC offers a streamlined approach with linear computational complexity, making it well-suited for large-scale network analysis. We further develop an LRC-based preprocessing method that effectively augments popular community detection algorithms. Through comprehensive simulations and applications on real-world datasets, including the NCAA football league network, the DBLP collaboration network, the Amazon product co-purchasing network, and the YouTube social network, we demonstrate the efficacy of our method in significantly improving the performance of various community detection algorithms.
Key facts. Cited by 2 papers in the map (data through 13 Oct 2026). First posted on arXiv 18 Jan 2024.
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Citing papers per year: 2024: 1; 2025: 1.
2 papers.
- 2024STNAGNN: Data-driven Spatio-temporal Brain Connectivity beyond FCcited by 3
- 2025Lower Ricci Curvature for Hypergraphscited by 0
- 2025Lower Ricci Curvature for Hypergraphs4 Jun 2025
- 2024STNAGNN: Data-driven Spatio-temporal Brain Connectivity beyond FC17 Jun 2024