2024/01/18 by Yun Jin Park, Park, Yun Jin, Didong Li +1 · 1 citation
Computer Science · Physics and Astronomy · #Applications (stat.AP) #Complex Network Analysis Techniques #FOS: Computer and information sciences #FOS: Physical sciences #Methodology (stat.ME) #Network Security and Intrusion Detection #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #Video Analysis and Summarization
paper · pdf · doi:10.48550/arxiv.2401.10124
openalex publication_date 2024/01/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.