• Corpus ID: 203593985

Changing the tune: mixtures of network models that vary in time

@article{Arnold2019ChangingTT,
  title={Changing the tune: mixtures of network models that vary in time},
  author={Naomi A. Arnold and Ra{\'u}l J. Mondrag{\'o}n and Richard G. Clegg},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.13253}
}
Many of the complex systems we study in their representation as networks are growing objects, evolving by the addition of nodes and links over time. The rules governing this growth are attributed to mechanisms such as preferential attachment and triangle closure. We demonstrate a method for estimating the relative roles of these mechanisms, and further, investigating how they change as the network evolves. We show that a rich class of network evolution models can be built from a weighted… 
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Identifying time dependence in network growth

The k2 model, an adaptation of the Barab{\'a}si-Albert model, is introduced, which results in time dependent degree distributions and attachment kernels, despite initially appearing to grow as linear preferential attachment, and without the need to include explicit time dependence in key network parameters (such as the average out-degree).

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