7,595 research outputs found
The effect of network structure on phase transitions in queuing networks
Recently, De Martino et al have presented a general framework for the study
of transportation phenomena on complex networks. One of their most significant
achievements was a deeper understanding of the phase transition from the
uncongested to the congested phase at a critical traffic load. In this paper,
we also study phase transition in transportation networks using a discrete time
random walk model. Our aim is to establish a direct connection between the
structure of the graph and the value of the critical traffic load. Applying
spectral graph theory, we show that the original results of De Martino et al
showing that the critical loading depends only on the degree sequence of the
graph -- suggesting that different graphs with the same degree sequence have
the same critical loading if all other circumstances are fixed -- is valid only
if the graph is dense enough. For sparse graphs, higher order corrections,
related to the local structure of the network, appear.Comment: 12 pages, 7 figure
The organization of the interbank network and how ECB unconventional measures affected the e-MID overnight market
The topological properties of interbank networks have been discussed widely
in the literature mainly because of their relevance for systemic risk. Here we
propose to use the Stochastic Block Model to investigate and perform a model
selection among several possible two block organizations of the network: these
include bipartite, core-periphery, and modular structures. We apply our method
to the e-MID interbank market in the period 2010-2014 and we show that in
normal conditions the most likely network organization is a bipartite
structure. In exceptional conditions, such as after LTRO, one of the most
important unconventional measures by ECB at the beginning of 2012, the most
likely structure becomes a random one and only in 2014 the e-MID market went
back to a normal bipartite organization. By investigating the strategy of
individual banks, we explore possible explanations and we show that the
disappearance of many lending banks and the strategy switch of a very small set
of banks from borrower to lender is likely at the origin of this structural
change.Comment: 33 pages, 5 figure
Self-organization of collaboration networks
We study collaboration networks in terms of evolving, self-organizing
bipartite graph models. We propose a model of a growing network, which combines
preferential edge attachment with the bipartite structure, generic for
collaboration networks. The model depends exclusively on basic properties of
the network, such as the total number of collaborators and acts of
collaboration, the mean size of collaborations, etc. The simplest model defined
within this framework already allows us to describe many of the main
topological characteristics (degree distribution, clustering coefficient, etc.)
of one-mode projections of several real collaboration networks, without
parameter fitting. We explain the observed dependence of the local clustering
on degree and the degree--degree correlations in terms of the ``aging'' of
collaborators and their physical impossibility to participate in an unlimited
number of collaborations.Comment: 10 pages, 8 figure
Correlations in Bipartite Collaboration Networks
Collaboration networks are studied as an example of growing bipartite
networks. These have been previously observed to have structure such as
positive correlations between nearest-neighbour degrees. However, a detailed
understanding of the origin of this phenomenon and the growth dynamics is
lacking. Both of these are analyzed empirically and simulated using various
models. A new one is presented, incorporating empirically necessary ingredients
such as bipartiteness and sublinear preferential attachment. This, and a
recently proposed model of team assembly both agree roughly with some empirical
observations and fail in several others.Comment: 13 pages, 17 figures, 2 table, submitted to JSTAT; manuscript
reorganized, figures and a table adde
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