3,643 research outputs found
The influence of persuasion in opinion formation and polarization
We present a model that explores the influence of persuasion in a population
of agents with positive and negative opinion orientations. The opinion of each
agent is represented by an integer number that expresses its level of
agreement on a given issue, from totally against to totally in favor
. Same-orientation agents persuade each other with probability ,
becoming more extreme, while opposite-orientation agents become more moderate
as they reach a compromise with probability . The population initially
evolves to (a) a polarized state for , where opinions' distribution is
peaked at the extreme values , or (b) a centralized state for ,
with most opinions around . When , polarization lasts for a
time that diverges as , where is the population's size. Finally,
an extremist consensus ( or ) is reached in a time that scales as
for
Log-mean linear models for binary data
This paper introduces a novel class of models for binary data, which we call
log-mean linear models. The characterizing feature of these models is that they
are specified by linear constraints on the log-mean linear parameter, defined
as a log-linear expansion of the mean parameter of the multivariate Bernoulli
distribution. We show that marginal independence relationships between
variables can be specified by setting certain log-mean linear interactions to
zero and, more specifically, that graphical models of marginal independence are
log-mean linear models. Our approach overcomes some drawbacks of the existing
parameterizations of graphical models of marginal independence
Interacting social processes on interconnected networks
We propose and study a model for the interplay between two different
dynamical processes --one for opinion formation and the other for decision
making-- on two interconnected networks and . The opinion dynamics on
network corresponds to that of the M-model, where the state of each agent
can take one of four possible values (), describing its level of
agreement on a given issue. The likelihood to become an extremist ()
or a moderate () is controlled by a reinforcement parameter .
The decision making dynamics on network is akin to that of the
Abrams-Strogatz model, where agents can be either in favor () or against
() the issue. The probability that an agent changes its state is
proportional to the fraction of neighbors that hold the opposite state raised
to a power . Starting from a polarized case scenario in which all agents
of network hold positive orientations while all agents of network have
a negative orientation, we explore the conditions under which one of the
dynamics prevails over the other, imposing its initial orientation. We find
that, for a given value of , the two-network system reaches a consensus
in the positive state (initial state of network ) when the reinforcement
overcomes a crossover value , while a negative consensus happens
for . In the phase space, the system displays a
transition at a critical threshold , from a coexistence of both
orientations for to a dominance of one orientation for
. We develop an analytical mean-field approach that gives an
insight into these regimes and shows that both dynamics are equivalent along
the crossover line .Comment: 25 pages, 6 figure
Exciton-phonon scattering and photo-excitation dynamics in J-aggregate microcavities
We have developed a model accounting for the photo-excitation dynamics and
the photoluminescence of strongly coupled J-aggregate microcavities. Our model
is based on a description of the J-aggregate film as a disordered Frenkel
exciton system in which relaxation occurs due to the presence of a thermal bath
of molecular vibrations. In a strongly coupled microcavity exciton-polaritons
are formed, mixing superradiant excitons and cavity photons. The calculation of
the microcavity steady-state photoluminescence, following a CW non resonant
pumping, is carried out. The experimental photoluminescence intensity ratio
between upper and lower polariton branches is accurately reproduced. In
particular both thermal activation of the photoluminescence intensity ratio and
its Rabi splitting dependence are a consequence of the bottleneck in the
relaxation, occurring at the bottom of the excitonic reservoir. The effects due
to radiative channels of decay of excitons and to the presence of a
paritticular set of discrete optical molecular vibrations active in relaxation
processes are investigared.Comment: 8 pages, 6 figure
Synchronization in interacting Scale Free Networks
We study the fluctuations of the interface, in the steady state, of the
Surface Relaxation Model (SRM) in two scale free interacting networks where a
fraction of nodes in both networks interact one to one through external
connections. We find that as increases the fluctuations on both networks
decrease and thus the synchronization reaches an improvement of nearly
when . The decrease of the fluctuations on both networks is due mainly to
the diffusion through external connections which allows to reducing the load in
nodes by sending their excess mostly to low-degree nodes, which we report have
the lowest heights. This effect enhances the matching of the heights of low-and
high-degree nodes as increases reducing the fluctuations. This effect is
almost independent of the degree distribution of the networks which means that
the interconnection governs the behavior of the process over its topology.Comment: 13 pages, 7 figures. Added a relevant reference.Typos fixe
Assessing skewness in financial markets
It is common knowledge that investors like large gains and dislike large losses.
This translates into a preference for right-skewed return distributions, with right tails heavier than left tails.
Skewness is thus interesting not only as a way to describe the shape of a distribution, but also for risk measurement.
We review the statistical literature on skewness and provide a comprehensive framework for its assessment.
We present a new measure of skewness, based on a relative comparison between above average and below average returns.
We show that this measure represents a valid complement to the state of the art
Assessing skewness in financial markets
It is a matter of common observation that investors value substantial gains but are averse to heavy losses. Obvious as it may sound, this translates into an interesting preference for right-skewed return distributions, whose right tails are heavier than their left tails. Skewness is thus not only a way to describe the shape of a distribution, but also a tool for risk measurement. We review the statistical literature on skewness and provide a comprehensive framework for its assessment. Then, we present a new measure of skewness, based on the decomposition of variance in its upward and downward components. We argue that this measure fills a gap in the literature and show in a simulation study that it strikes a good balance between robustness and sensitivity
Recovery of Interdependent Networks
Recent network research has focused on the cascading failures in a system of
interdependent networks and the necessary preconditions for system collapse. An
important question that has not been addressed is how to repair a failing
system before it suffers total breakdown. Here we introduce a recovery strategy
of nodes and develop an analytic and numerical framework for studying the
concurrent failure and recovery of a system of interdependent networks based on
an efficient and practically reasonable strategy. Our strategy consists of
repairing a fraction of failed nodes, with probability of recovery ,
that are neighbors of the largest connected component of each constituent
network. We find that, for a given initial failure of a fraction of
nodes, there is a critical probability of recovery above which the cascade is
halted and the system fully restores to its initial state and below which the
system abruptly collapses. As a consequence we find in the plane of
the phase diagram three distinct phases. A phase in which the system never
collapses without being restored, another phase in which the recovery strategy
avoids the breakdown, and a phase in which even the repairing process cannot
avoid the system collapse
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