ArticleScientific reports2019
Ollivier-Ricci Curvature-Based Method to Community Detection in Complex Networks.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 106 citations in OpenAlex.
- Graph Ricci curvatures reveal atypical functional connectivity in autism spectrum disorder.Scientific reports · 2022Pooled it
- Optimizing Solid Lubricity in Complex Particle Flow.ACS materials Au · 2026Article
- HyMSS-GAD: a hybrid multi-stage framework for multi-view graph anomaly detection with structural, contextual, and geometric reasoning.Scientific reports · 2026Article
- Lower Ricci Curvature for Efficient Community Detection.Transactions on machine learning research · 2025Article
- Characterizing Physician Referral Networks with Ricci Curvature.Pediatric and lifespan data science : First International Conference, IPLDSC 2024, Anaheim, CA, USA, May 23-24, 2024, Revised Selected Papers. International Pediatric and Lifespan Data Science Conference (1st : 2024 : Anaheim, Calif.) · 2025Article
- Curvature-enhanced graph convolutional network for biomolecular interaction prediction.Computational and structural biotechnology journal · 2024Article
- Community detection in the human connectome: Method types, differences and their impact on inference.Human brain mapping · 2024Article
- Charting cellular differentiation trajectories with Ricci flow.Nature communications · 2024Article
- Multi-scale geometric network analysis identifies melanoma immunotherapy response gene modules.Scientific reports · 2024Article
- Multi-Scale Geometric Network Analysis Identifies Melanoma Immunotherapy Response Gene Modules.bioRxiv : the preprint server for biology · 2023Article
- A unified approach of detecting phase transition in time-varying complex networks.Scientific reports · 2023Article
- Structure-based prediction of nucleic acid binding residues by merging deep learning- and template-based approaches.PLoS computational biology · 2023Article
- Deeper Exploiting Graph Structure Information by Discrete Ricci Curvature in a Graph Transformer.Entropy (Basel, Switzerland) · 2023Article
- Discrete Ricci curvatures capture age-related changes in human brain functional connectivity networks.Frontiers in aging neuroscience · 2023Article
- Diffusion Curvature for Estimating Local Curvature in High Dimensional Data.Advances in neural information processing systems · 2022Article
- Community detection in networks by dynamical optimal transport formulation.Scientific reports · 2022Article
- Inferring functional communities from partially observed biological networks exploiting geometric topology and side information.Scientific reports · 2022Article
- Deciphering the generating rules and functionalities of complex networks.Scientific reports · 2021Article
- Understanding Changes in the Topology and Geometry of Financial Market Correlations during a Market Crash.Entropy (Basel, Switzerland) · 2021Article
- Unfolding the multiscale structure of networks with dynamical Ollivier-Ricci curvature.Nature communications · 2021Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identification of community structures in complex network is of crucial importance for understanding the system's function, organization, robustness and security. Here, we present a novel Ollivier-Ricci curvature (ORC) inspired approach to community identification in complex networks. We demonstrate that the intrinsic geometric underpinning of the ORC offers a natural approach to discover inherent community structures within a network based on interaction among entities. We develop an ORC-based community identification algorithm based on the idea of sequential removal of negatively curved edges symptomatic of high interactions (e.g., traffic, attraction). To illustrate and compare the performance with other community identification methods, we examine the ORC-based algorithm with stochastic block model artificial networks and real-world examples ranging from social to drug-drug interaction networks. The ORC-based algorithm is able to identify communities with either better or comparable performance accuracy and to discover finer hierarchical structures of the network. This opens new geometric avenues for analysis of complex networks dynamics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.