Emergence of Soft Communities from Geometric Preferential Attachment
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Abstract (arXiv)
All real networks are different, but many have some structural properties in common. There seems to be no consensus on what the most common properties are, but scale-free degree distributions, strong clustering, and community structure are frequently mentioned without question. Surprisingly, there exists no simple generative mechanism explaining all the three properties at once in growing networks. Here we show how latent network geometry coupled with preferential attachment of nodes to this geometry fills this gap. We call this mechanism geometric preferential attachment (GPA), and validate it against the Internet. GPA gives rise to soft communities that provide a different perspective on the community structure in networks. The connections between GPA and cosmological models, including inflation, are also discussed.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Jan 2015.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 3; 2025: 1; 2026: 1.
8 papers.
- 2021A Multi-purposed Unsupervised Framework for Comparing Embeddings of Undirected and Directed Graphscited by 6
- 2021Evaluating Node Embeddings of Complex Networkscited by 4
- 2023Zoo Guide to Network Embeddingcited by 2
- 2024Symmetry-driven embedding of networks in hyperbolic spacecited by 1
- 2025Beyond MMD: Evaluating Graph Generative Models with Geometric Deep Learningcited by 1
- 2024Hyperbolic Benchmarking Unveils Network Topology-Feature Relationship in GNN Performancecited by 0
- 2024Uncovering the hidden core-periphery structure in hyperbolic networkscited by 0
- 2026Bayesian Latent Space Models for Graphs Are Misspecified: Toward Robust Inference via Generalized Posteriorscited by 0
- 2026Bayesian Latent Space Models for Graphs Are Misspecified: Toward Robust Inference via Generalized Posteriors18 May 2026
- 2025Beyond MMD: Evaluating Graph Generative Models with Geometric Deep Learning16 Dec 2025
- 2024Uncovering the hidden core-periphery structure in hyperbolic networks28 Jun 2024
- 2024Symmetry-driven embedding of networks in hyperbolic space15 Jun 2024
- 2024Hyperbolic Benchmarking Unveils Network Topology-Feature Relationship in GNN Performance4 Jun 2024
- 2023Zoo Guide to Network Embedding5 May 2023
- 2021A Multi-purposed Unsupervised Framework for Comparing Embeddings of Undirected and Directed Graphs30 Nov 2021
- 2021Evaluating Node Embeddings of Complex Networks16 Feb 2021