Abstract
Integral to the problem of detecting communities through graph clustering is the expectation that they are “well-connected”. Surprisingly, we find that the output of multiple clustering approaches–the Leiden algorithm with either the Constant Potts Model or modularity as quality function, Iterative K-Core Clustering, Infomap, and Markov Clustering–include communities that fail even a mild requirement for well-connectedness. As a remediation strategy, we have developed the “Connectivity Modifier” (CM), which iteratively removes small edge cuts and re-clusters until all communities detected are well-connected. Results from real-world networks with up to 75,025,194 nodes illustrate how CM enables additional insights into community structure within networks, while results on synthetic networks show that the CM algorithm improves accuracy in recovering true communities. Our study also raises questions about the “clusterability” of networks and mathematical models of community structure.
Original language | English (US) |
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Title of host publication | Complex Networks and Their Applications XII - Proceedings of The 12th International Conference on Complex Networks and their Applications |
Subtitle of host publication | COMPLEX NETWORKS 2023 |
Editors | Hocine Cherifi, Luis M. Rocha, Chantal Cherifi, Murat Donduran |
Publisher | Springer |
Pages | 3-14 |
Number of pages | 12 |
ISBN (Print) | 9783031534980 |
DOIs | |
State | Published - 2024 |
Event | 12th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2023 - Menton, France Duration: Nov 28 2023 → Nov 30 2023 |
Publication series
Name | Studies in Computational Intelligence |
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Volume | 1142 SCI |
ISSN (Print) | 1860-949X |
ISSN (Electronic) | 1860-9503 |
Conference
Conference | 12th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2023 |
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Country/Territory | France |
City | Menton |
Period | 11/28/23 → 11/30/23 |
Keywords
- citation networks
- community detection
- connectivity
ASJC Scopus subject areas
- Artificial Intelligence
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Dive into the research topics of 'Identifying Well-Connected Communities in Real-World and Synthetic Networks'. Together they form a unique fingerprint.Datasets
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Data for Well-Connectedness and Community Detection
Park, M. (Creator), Tabatabaee, Y. (Creator), Warnow, T. (Creator) & Chacko, G. (Creator), University of Illinois Urbana-Champaign, Jun 4 2024
DOI: 10.13012/B2IDB-6271968_V1
Dataset