2,701 research outputs found
Cascade control and defense in complex networks
Complex networks with heterogeneous distribution of loads may undergo a
global cascade of overload failures when highly loaded nodes or edges are
removed due to attacks or failures. Since a small attack or failure has the
potential to trigger a global cascade, a fundamental question regards the
possible strategies of defense to prevent the cascade from propagating through
the entire network. Here we introduce and investigate a costless strategy of
defense based on a selective further removal of nodes and edges, right after
the initial attack or failure. This intentional removal of network elements is
shown to drastically reduce the size of the cascade.Comment: 4 pages, 2 figures, Revte
Efficient local strategies for vaccination and network attack
We study how a fraction of a population should be vaccinated to most
efficiently top epidemics. We argue that only local information (about the
neighborhood of specific vertices) is usable in practice, and hence we consider
only local vaccination strategies. The efficiency of the vaccination strategies
is investigated with both static and dynamical measures. Among other things we
find that the most efficient strategy for many real-world situations is to
iteratively vaccinate the neighbor of the previous vaccinee that has most links
out of the neighborhood
Tax evasion dynamics and Zaklan model on Opinion-dependent Network
Within the context of agent-based Monte-Carlo simulations, we study the
well-known majority-vote model (MVM) with noise applied to tax evasion on
Stauffer-Hohnisch-Pittnauer (SHP) networks. To control the fluctuations for tax
evasion in the economics model proposed by Zaklan, MVM is applied in the
neighborhood of the critical noise to evolve the Zaklan model. The
Zaklan model had been studied recently using the equilibrium Ising model. Here
we show that the Zaklan model is robust because this can be studied besides
using equilibrium dynamics of Ising model also through the nonequilibrium MVM
and on various topologies giving the same behavior regardless of dynamic or
topology used here.Comment: 14 page, 4 figure
Network dynamics of ongoing social relationships
Many recent large-scale studies of interaction networks have focused on
networks of accumulated contacts. In this paper we explore social networks of
ongoing relationships with an emphasis on dynamical aspects. We find a
distribution of response times (times between consecutive contacts of different
direction between two actors) that has a power-law shape over a large range. We
also argue that the distribution of relationship duration (the time between the
first and last contacts between actors) is exponentially decaying. Methods to
reanalyze the data to compensate for the finite sampling time are proposed. We
find that the degree distribution for networks of ongoing contacts fits better
to a power-law than the degree distribution of the network of accumulated
contacts do. We see that the clustering and assortative mixing coefficients are
of the same order for networks of ongoing and accumulated contacts, and that
the structural fluctuations of the former are rather large.Comment: to appear in Europhys. Let
Modularity and community structure in networks
Many networks of interest in the sciences, including a variety of social and
biological networks, are found to divide naturally into communities or modules.
The problem of detecting and characterizing this community structure has
attracted considerable recent attention. One of the most sensitive detection
methods is optimization of the quality function known as "modularity" over the
possible divisions of a network, but direct application of this method using,
for instance, simulated annealing is computationally costly. Here we show that
the modularity can be reformulated in terms of the eigenvectors of a new
characteristic matrix for the network, which we call the modularity matrix, and
that this reformulation leads to a spectral algorithm for community detection
that returns results of better quality than competing methods in noticeably
shorter running times. We demonstrate the algorithm with applications to
several network data sets.Comment: 7 pages, 3 figure
Network reachability of real-world contact sequences
We use real-world contact sequences, time-ordered lists of contacts from one
person to another, to study how fast information or disease can spread across
network of contacts. Specifically we measure the reachability time -- the
average shortest time for a series of contacts to spread information between a
reachable pair of vertices (a pair where a chain of contacts exists leading
from one person to the other) -- and the reachability ratio -- the fraction of
reachable vertex pairs. These measures are studied using conditional uniform
graph tests. We conclude, among other things, that the network reachability
depends much on a core where the path lengths are short and communication
frequent, that clustering of the contacts of an edge in time tend to decrease
the reachability, and that the order of the contacts really do make sense for
dynamical spreading processes.Comment: (v2: fig. 1 fixed
Role of Activity in Human Dynamics
The human society is a very complex system; still, there are several
non-trivial, general features. One type of them is the presence of power-law
distributed quantities in temporal statistics. In this Letter, we focus on the
origin of power-laws in rating of movies. We present a systematic empirical
exploration of the time between two consecutive ratings of movies (the
interevent time). At an aggregate level, we find a monotonous relation between
the activity of individuals and the power-law exponent of the interevent-time
distribution. At an individual level, we observe a heavy-tailed distribution
for each user, as well as a negative correlation between the activity and the
width of the distribution. We support these findings by a similar data set from
mobile phone text-message communication. Our results demonstrate a significant
role of the activity of individuals on the society-level patterns of human
behavior. We believe this is a common character in the interest-driven human
dynamics, corresponding to (but different from) the universality classes of
task-driven dynamics.Comment: 5 pages, 6 figures. Accepted by EP
A network-based threshold model for the spreading of fads in society and markets
We investigate the behavior of a threshold model for the spreading of fads
and similar phenomena in society. The model is giving the fad dynamics and is
intended to be confined to an underlying network structure. We investigate the
whole parameter space of the fad dynamics on three types of network models. The
dynamics we discover is rich and highly dependent on the underlying network
structure. For some range of the parameter space, for all types of substrate
networks, there are a great variety of sizes and life-lengths of the fads --
what one see in real-world social and economical systems
- …