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Inverse Resolution Limit of Partition Density and Detecting Overlapping Communities by Link-Surprise
Cited 6 time in
Web of Science
Cited 8 time in Scopus
- Authors
- Issue Date
- 2017-09
- Publisher
- Nature Publishing Group
- Citation
- Scientific Reports, Vol.7, p. 12399
- Abstract
- Finding overlapping communities of complex networks remains a challenge in network science. To address this challenge, one of the widely used approaches is finding the communities of links by optimizing the objective function, partition density. In this study, we show that partition density suffers from inverse resolution limit; it has a strong preference to triangles. This resolution limit makes partition density an improper objective function for global optimization. The conditions where partition density prefers triangles to larger link community structures are analytically derived and confirmed with global optimization calculations using synthetic and real-world networks. To overcome this limitation of partition density, we suggest an alternative measure, Link Surprise, to find link communities, which is suitable for global optimization. Benchmark studies demonstrate that global optimization of Link Surprise yields meaningful and more accurate link community structures than partition density optimization.
- ISSN
- 2045-2322
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Related Researcher
- Graduate School of Convergence Science & Technology
- Dept. of Molecular and Biopharmaceutical Sciences
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