The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
A faster algorithm for betweenness centrality*
Open accessAbstract
Motivated by the fast‐growing need to compute centrality indices on large, yet very sparse, networks, new algorithms for betweenness are introduced in this paper. They require O(n + m) space and run in O(nm) and O(nm + n2 log n) time on unweighted and weighted networks, respectively, where m is the number of links. Experimental evidence is provided that this substantially increases the range of networks for which centrality analysis is feasible. The betweenness centrality index is essential in the analysis of social networks, but costly to compute. Currently, the fastest known algorithms require ?(n 3) time and ?(n 2) space, where n is the number of actors in the network.
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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
Complex network measures of brain connectivity: Uses and interpretations
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Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Network analysis: An integrative approach to the structure of psychopathology
Borsboom, D., & Cramer, A. O. J. (2013) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-050212-185608 · Cited by 4,359
Defining 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
Metadata
- Authors
- Brandes, U.
- Venue
- The Journal of Mathematical Sociology
- Publisher
- Informa UK Limited
- Published
- 2001-06
- Volume
- 25
- Issue
- 2
- Pages
- 163-177
- ISSN
- 0022-250X (ISSN-L)
- 1545-5874
- OpenAlex
- W2171707538
- Cited by
- 4,936
- References
- 28
- FWCI
- 11.14
- Type
- journal article
- Language
- en
- Open access
- green
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