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The magic of networks grown by redirection

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Abstract

We highlight intriguing features of complex networks that are grown by redirection. In this mechanism, a target node is chosen uniformly at random from the pre-existing network nodes and the new node attaches either to this initial target or to a neighbor of this target. This exceedingly simple algorithm generates preferential attachment networks in an algorithmic time that is linear in the number of network nodes N. Even though preferential attachment ostensibly requires global knowledge of the network, redirection requires only local knowledge. We also show that changing just a single attachment rate in linear preferential attachment leads to a non-universal degree distribution. Finally, we present unexpected consequences of redirection in networks with undirected links, where highly modular and non-sparse networks arise.

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Authors and Affiliations

  1. Department of Physics, Boston University, Boston, MA, 02215, USA

    P. L. Krapivsky

  2. Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM, 87501, USA

    P. L. Krapivsky & S. Redner

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  1. P. L. Krapivsky
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  2. S. Redner
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Krapivsky, P.L., Redner, S. The magic of networks grown by redirection. Indian J Phys (2023). https://doi.org/10.1007/s12648-023-02874-x

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