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Erschienen in: Journal of Economic Interaction and Coordination 3/2019

27.09.2018 | Regular Article

Degree-correlations in a bursting dynamic network model

verfasst von: Fabio Vanni, Paolo Barucca

Erschienen in: Journal of Economic Interaction and Coordination | Ausgabe 3/2019

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Abstract

We propose a mathematical description of a dynamic network model in which the number of links fluctuates over time according to the degree-preferences of nodes. More specifically, we consider the minimal case of a bipartite directed network where we have two groups of nodes, each group has nodes with a given capability to bear links. One group is composed of nodes that create as many links as possible, the generators. The other group is composed of nodes which delete as many links as possible, i.e., the destroyers. We provide here a novel analytical formulation of the evolution of the system through coupled master equations for the two interacting populations, recovering the steady state degree distributions and a new analytic description of the transient dynamics to the equilibrium. Further, fluctuations are shown to be connected to a peak in degree correlation at a critical point of the system corresponding to equal-size populations of generators and destroyers. We investigate the nature of the neighbor connectivity and the temporal assortativity of the network, noticing that degree correlation are anomalously large at criticality and that they are not a pointwise characterization of the system in time but they emerge as an aggregate temporal property. Moreover, we examine the bursty dynamics of the network as a temporal property where the system heterogeneously evolves over time alternating between periods of low and high connectivity displaying a heavy-tailed distribution in the inter-event times distributions. Finally, we introduce a generalization of the model in which intermittent states can control the velocity of the network’s evolution. We will also provide examples of possible economic applications of the present network model.

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Fußnoten
1
Note the the normalization factor of the mean is not T, since we do not count the case in which there are no nodes with a given ANND for a time snapshot t. In the case in which in each timestep we always find an ANND for the associated degree k then we have \(N_k=T\). However, in general, this is not the case.
 
2
The connectance is defined as the link density of the network, which is the fraction of the number of actual links over the number of potential links between pairs of nodes. By the term connectivity, we indicate a generic property which gives a measure of the number of links in the network.
 
3
The stationary degree distribution can also be recovered just using the ordinary CMED approach as in Eq. (1) and using an event-based representation of temporal networks (Masuda and Lambiotte 2016). We can here modify the transition rates defining: \( \tilde{\varGamma }^+[k-1] = \varGamma ^+[k-1] (1-\lambda )\) and \(\tilde{\varGamma }^-[k,t] = \varGamma ^-[k,t] (1-\lambda )\). The problem with this approach is that we ignore the idle states and that the process has pauses in its trajectories. But, in the end, it reaches, with different transient times, the same degree distribution as using the intermittent CMED.
 
4
For \(N_0\rightarrow \infty \) we can write \(\sum \nolimits _{j=1}^{N_0}\frac{a^j}{j!}\approx e^a -1\), yielding the Zero-truncated Poisson distribution:
$$\begin{aligned} \rho ^{st}_{1}(k)=\frac{\chi ^k}{(e^{\chi }-1)}\frac{1}{k!} , \quad k=0\ldots N_0. \end{aligned}$$
 
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Metadaten
Titel
Degree-correlations in a bursting dynamic network model
verfasst von
Fabio Vanni
Paolo Barucca
Publikationsdatum
27.09.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Journal of Economic Interaction and Coordination / Ausgabe 3/2019
Print ISSN: 1860-711X
Elektronische ISSN: 1860-7128
DOI
https://doi.org/10.1007/s11403-018-0232-9

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