The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Community detection algorithms: A comparative analysis
Open accessAbstract
Uncovering the community structure exhibited by real networks is a crucial step toward an understanding of complex systems that goes beyond the local organization of their constituents. Many algorithms have been proposed so far, but none of them has been subjected to strict tests to evaluate their performance. Most of the sporadic tests performed so far involved small networks with known community structure and/or artificial graphs with a simplified structure, which is very uncommon in real systems. Here we test several methods against a recently introduced class of benchmark graphs, with heterogeneous distributions of degree and community size. The methods are also tested against the benchmark by Girvan and Newman [Proc. Natl. Acad. Sci. U.S.A. 99, 7821 (2002)] and on random graphs. As a result of our analysis, three recent algorithms introduced by Rosvall and Bergstrom [Proc. Natl. Acad. Sci. U.S.A. 104, 7327 (2007); Proc. Natl. Acad. Sci. U.S.A. 105, 1118 (2008)], Blondel [J. Stat. Mech.: Theory Exp. (2008), P10008], and Ronhovde and Nussinov [Phys. Rev. E 80, 016109 (2009)] have an excellent performance, with the additional advantage of low computational complexity, which enables one to analyze large systems.
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Cites
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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
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Self-citationNetwork motifs: simple building blocks of complex networks.
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Uncovering the overlapping community structure of complex networks in nature and society
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Functional cartography of complex metabolic networks
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Resolution limit in community detection
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Self-citationDefining and identifying communities in networks
Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., & Parisi, D. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400054101 · Cited by 2,450
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Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Self-citationFrom Louvain to Leiden: guaranteeing well-connected communities
Traag, V. A., Waltman, L., & van Eck, N. J. (2019) · Scientific Reports · doi:10.1038/s41598-019-41695-z · Cited by 5,635
Functional Network Organization of the Human Brain
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Community detection in networks: a user guide
Fortunato, S., & Hric, D. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.09.002 · Cited by 2,086
Self-citationSporns, O., & Betzel, R. F. (2016) · Annual Review of Psychology · doi:10.1146/annurev-psych-122414-033634 · Cited by 1,334
Metadata
- Authors
- Lancichinetti, A., & Fortunato, S.
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 2009-11-30
- Volume
- 80
- Issue
- 5
- Pages
- 056117-056117
- ISSN
- 1539-3755 (ISSN-L)
- 1550-2376
- OpenAlex
- W1995996823
- Cited by
- 2,177
- References
- 8
- FWCI
- 62.31
- Type
- journal article
- Language
- en
- Open access
- green
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