Abstract
Inspired by empirical studies of networked systems such as the Internet,\nsocial networks, and biological networks, researchers have in recent years\ndeveloped a variety of techniques and models to help us understand or predict\nthe behavior of these systems. Here we review developments in this field,\nincluding such concepts as the small-world effect, degree distributions,\nclustering, network correlations, random graph models, models of network growth\nand preferential attachment, and dynamical processes taking place on networks.\n
Keywords
Random graphComplex networkComputer scienceCluster analysisDegree distributionPreferential attachmentClustering coefficientBiological networkVariety (cybernetics)Evolving networksThe InternetField (mathematics)Theoretical computer scienceNetwork scienceSmall-world networkNetwork formationData scienceGraphArtificial intelligenceMathematicsWorld Wide Web
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Publication Info
- Year
- 2003
- Type
- article
- Volume
- 45
- Issue
- 2
- Pages
- 167-256
- Citations
- 18282
- Access
- Closed
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Cite This
Michael Newman
(2003).
The Structure and Function of Complex Networks.
SIAM Review
, 45
(2)
, 167-256.
https://doi.org/10.1137/s003614450342480
Identifiers
- DOI
- 10.1137/s003614450342480