138 research outputs found
Asymmetry of social interactions and its role in link predictability: the case of coauthorship networks
The paper provides important insights into understanding the factors that
influence tie strength in social networks. Using local network measures that
take into account asymmetry of social interactions we show that the observed
tie strength is a kind of compromise, which depends on the relative strength of
the tie as seen from its both ends. This statement is supported by the
Granovetter-like, strongly positive weight-topology correlations, in the form
of a power-law relationship between the asymmetric tie strength and asymmetric
neighbourhood overlap, observed in three different real coauthorship networks
and in a synthetic model of scientific collaboration. This observation is
juxtaposed against the current misconception that coauthorship networks, being
the proxy of scientific collaboration networks, contradict the Granovetter's
strength of weak ties hypothesis, and the reasons for this misconception are
explained. Finally, by testing various link similarity scores, it is shown that
taking into account the asymmetry of social ties can remarkably increase the
efficiency of link prediction methods. The perspective outlined also allows us
to comment on the surprisingly high performance of the resource allocation
index -- one of the most recognizable and effective local similarity scores --
which can be rationalized by the strong triadic closure property, assuming that
the property takes into account the asymmetry of social ties
Percolation in the classical blockmodel
Classical blockmodel is known as the simplest among models of networks with
community structure. The model can be also seen as an extremely simply example
of interconnected networks. For this reason, it is surprising that the
percolation transition in the classical blockmodel has not been examined so
far, although the phenomenon has been studied in a variety of much more
complicated models of interconnected and multiplex networks. In this paper we
derive the self-consistent equation for the size the global percolation cluster
in the classical blockmodel. We also find the condition for percolation
threshold which characterizes the emergence of the giant component. We show
that the discussed percolation phenomenon may cause unexpected problems in a
simple optimization process of the multilevel network construction. Numerical
simulations confirm the correctness of our theoretical derivations.Comment: 7 pages, 6 figure
Theoretical approach and impact of correlations on the critical packet generation rate in traffic dynamics on complex networks
Using the formalism of the biased random walk in random uncorrelated networks
with arbitrary degree distributions, we develop theoretical approach to the
critical packet generation rate in traffic based on routing strategy with local
information. We explain microscopic origins of the transition from the flow to
the jammed phase and discuss how the node neighbourhood topology affects the
transport capacity in uncorrelated and correlated networks.Comment: 6 pages, 5 figure
Phase transitions in social networks
We study a model of network with clustering and desired node degree. The
original purpose of the model was to describe optimal structures of scientific
collaboration in the European Union. The model belongs to the family of
exponential random graphs. We show by numerical simulations and analytical
considerations how a very simple Hamiltonian can lead to surprisingly
complicated and eventful phase diagram.Comment: 8 pages, 8 figure
A minimal model for congestion phenomena on complex networks
We study a minimal model of traffic flows in complex networks, simple enough
to get analytical results, but with a very rich phenomenology, presenting
continuous, discontinuous as well as hybrid phase transitions between a
free-flow phase and a congested phase, critical points and different scaling
behaviors in the system size. It consists of random walkers on a queueing
network with one-range repulsion, where particles can be destroyed only if they
can move. We focus on the dependence on the topology as well as on the level of
traffic control. We are able to obtain transition curves and phase diagrams at
analytical level for the ensemble of uncorrelated networks and numerically for
single instances. We find that traffic control improves global performance,
enlarging the free-flow region in parameter space only in heterogeneous
networks. Traffic control introduces non-linear effects and, beyond a critical
strength, may trigger the appearance of a congested phase in a discontinuous
manner. The model also reproduces the cross-over in the scaling of traffic
fluctuations empirically observed in the Internet, and moreover, a conserved
version can reproduce qualitatively some stylized facts of traffic in
transportation networks
Coexistence of bicuspid aortic valve, aberrant right subclavian artery and common origin of carotid arteries
Background: Prevalence of bicuspid aortic valve (BAV) and right aberrant sub-clavian artery (ASA) separately is relatively common in general population, and much higher in some disorders. Surprisingly, coexistence of both valve and vessel anomalies has only been reported in single cases.
Materials and methods: From 2008 to 2016, in a single, high-volume tertiary cardiac centre, patients who underwent chest computed tomography (CT) for various reasons, were retrospectively screened for the presence of right ASA.
Results: Seventy-two patients with either right or left ASA were identified by CT. Among them 7 cases of BAV and right ASA coexistence were identified. Additionally, 1 case with coexisting common origin of carotid arteries (COCA) was visualised in this subgroup.
Conclusions: Although coexistence of ASA and BAV has not been reported in paediatric population, it has been diagnosed in very few adults as well as in our series. Additional presence of COCA in this group seems to be very rare. From practical point of view, heart cannulation via the radial artery and subsequent ASA may be challenging. Similarly, COCA presence may have surgical implications during corrective procedures
Self-organized network evolution coupled to extremal dynamics
The interplay between topology and dynamics in complex networks is a
fundamental but widely unexplored problem. Here, we study this phenomenon on a
prototype model in which the network is shaped by a dynamical variable. We
couple the dynamics of the Bak-Sneppen evolution model with the rules of the
so-called fitness network model for establishing the topology of a network;
each vertex is assigned a fitness, and the vertex with minimum fitness and its
neighbours are updated in each iteration. At the same time, the links between
the updated vertices and all other vertices are drawn anew with a
fitness-dependent connection probability. We show analytically and numerically
that the system self-organizes to a non-trivial state that differs from what is
obtained when the two processes are decoupled. A power-law decay of dynamical
and topological quantities above a threshold emerges spontaneously, as well as
a feedback between different dynamical regimes and the underlying correlation
and percolation properties of the network.Comment: Accepted version. Supplementary information at
http://www.nature.com/nphys/journal/v3/n11/suppinfo/nphys729_S1.htm
Evolutionary Events in a Mathematical Sciences Research Collaboration Network
This study examines long-term trends and shifting behavior in the
collaboration network of mathematics literature, using a subset of data from
Mathematical Reviews spanning 1985-2009. Rather than modeling the network
cumulatively, this study traces the evolution of the "here and now" using
fixed-duration sliding windows. The analysis uses a suite of common network
diagnostics, including the distributions of degrees, distances, and clustering,
to track network structure. Several random models that call these diagnostics
as parameters help tease them apart as factors from the values of others. Some
behaviors are consistent over the entire interval, but most diagnostics
indicate that the network's structural evolution is dominated by occasional
dramatic shifts in otherwise steady trends. These behaviors are not distributed
evenly across the network; stark differences in evolution can be observed
between two major subnetworks, loosely thought of as "pure" and "applied",
which approximately partition the aggregate. The paper characterizes two major
events along the mathematics network trajectory and discusses possible
explanatory factors.Comment: 30 pages, 14 figures, 1 table; supporting information: 5 pages, 5
figures; published in Scientometric
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