Posted in 2022

Random link-activation temporal network with Reticula

For the past few years, I have been studying properties of temporal networks and how certain inhomogeneities affect the nature and extent of connectivity in them. The most straightforward avenue of attacking this problem is to construct a random temporal network using a generative model that includes the desired spatial or temporal property, for example burstiness or degree inhomogeneity, and comparing the connectivity to temporal networks generated through methods that don’t include that property. In this post I’ll go through my current go-to family of models, link-activation temporal networks, as well as how you can use them in the Reticula network analysis library.

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