The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Detecting the overlapping and hierarchical community structure in complex networks
Open accessAbstract
Many networks in nature, society and technology are characterized by a mesoscopic level of organization, with groups of nodes forming tightly connected units, called communities or modules, that are only weakly linked to each other. Uncovering this community structure is one of the most important problems in the field of complex networks. Networks often show a hierarchical organization, with communities embedded within other communities; moreover, nodes can be shared between different communities. Here, we present the first algorithm that finds both overlapping communities and the hierarchical structure. The method is based on the local optimization of a fitness function. Community structure is revealed by peaks in the fitness histogram. The resolution can be tuned by a parameter enabling different hierarchical levels of organization to be investigated. Tests on real and artificial networks give excellent results.
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Cites
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Self-citationDefining and identifying communities in networks
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Cited by
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Self-citationCommunity 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-citationLine graphs, link partitions, and overlapping communities
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Tracking the Evolution of Communities in Dynamic Social Networks
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Metadata
- Authors
- Lancichinetti, A., Fortunato, S., & Kertész, J.
- Venue
- New Journal of Physics
- Publisher
- IOP Publishing
- Published
- 2009-03-10
- Volume
- 11
- Issue
- 3
- Pages
- 033015
- ISSN
- 1367-2630 (ISSN-L)
- OpenAlex
- W2118608338
- Cited by
- 1,941
- References
- 11
- FWCI
- 62.07
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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