The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Bayesian Approach to Network Modularity
Open accessAbstract
We present an efficient, principled, and interpretable technique for inferring module assignments and for identifying the optimal number of modules in a given network. We show how several existing methods for finding modules can be described as variant, special, or limiting cases of our work, and how the method overcomes the resolution limit problem, accurately recovering the true number of modules. Our approach is based on Bayesian methods for model selection which have been used with success for almost a century, implemented using a variational technique developed only in the past decade. We apply the technique to synthetic and real networks and outline how the method naturally allows selection among competing models.
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Citations
Cites
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
Kass, R. E., & Raftery, A. E. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476572 · Cited by 12,558
An Introduction to Variational Methods for Graphical Models
Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., & Saul, L. K. (1999) · Machine Learning · doi:10.1023/a:1007665907178 · Cited by 3,791
Resolution limit in community detection
Fortunato, S., & Barthélemy, M. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605965104 · Cited by 3,024
Statistical Mechanics: A Set of Lectures
Feynman, R. P., & Lebowitz, J. L. (1973) · Physics Today · doi:10.1063/1.3128279 · Cited by 423
Cited by
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Stochastic blockmodels and community structure in networks
Karrer, B., & Newman, M. E. J. (2011) · Physical Review E · doi:10.1103/physreve.83.016107 · Cited by 2,025
Performance of modularity maximization in practical contexts
Good, B. H., de Montjoye, Y.-A., & Clauset, A. (2010) · Physical Review E · doi:10.1103/physreve.81.046106 · Cited by 937
Communities, modules and large-scale structure in networks
Newman, M. E. J. (2012) · Nature Physics · doi:10.1038/nphys2162 · Cited by 787
Combining link and content for community detection: a discriminative approach
Yang, T., Jin, R., Chi, Y., & Zhu, S. (2009) · Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1557019.1557120 · Cited by 364
Metadata
- Authors
- Hofman, J. M., & Wiggins, C. H.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 2008-06-23
- Volume
- 100
- Issue
- 25
- Pages
- 258701-258701
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W2116433231
- Cited by
- 298
- References
- 5
- FWCI
- 25.14
- Type
- journal article
- Language
- en
- Open access
- green
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