The Structure and Function of Complex Networks
Michael Newman
Abstract
Inspired by empirical studies of networked systems such as the Internet, social networks, and bio-logical networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world eect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Topics & Concepts
Random graphComplex networkComputer scienceCluster analysisDegree distributionPreferential attachmentClustering coefficientBiological networkVariety (cybernetics)Evolving networksThe InternetField (mathematics)Theoretical computer scienceNetwork scienceSmall-world networkNetwork formationData scienceGraphArtificial intelligenceMathematicsWorld Wide WebPure mathematicsCombinatoricsComplex Network Analysis TechniquesOpinion Dynamics and Social InfluenceGame Theory and Applications