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Clustering and preferential attachment in growing networks

M. E. J. Newman

Abstract

We study empirically the time evolution of scientific collaboration networks in physics and biology. In these networks, two scientists are considered connected if they have coauthored one or more papers together. We show that the probability of a pair of scientists collaborating increases with the number of other collaborators they have in common, and that the probability of a particular scientist acquiring new collaborators increases with the number of his or her past collaborators. These results provide experimental evidence in favor of previously conjectured mechanisms for clustering and power-law degree distributions in networks.

Complex Network Analysis TechniquesOpinion Dynamics and Social InfluenceBioinformatics and Genomic NetworksCluster analysisPreferential attachmentProbability and statisticsComplex networkComputer scienceData scienceStatistical physicsMathematicsPhysicsArtificial intelligence
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