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 $k$ that expresses its level of agreement on a given issue, from totally against $k=-M$ to totally in favor $k=M$. Same-orientation agents persuade each other with probability $p$, becoming more extreme, while opposite-orientation agents become more moderate as they reach a compromise with probability $q$. The population initially evolves to (a) a polarized state for $r=p/q>1$, where opinions' distribution is peaked at the extreme values $k=\pm M$, or (b) a centralized state for $r<1$, with most opinions around $k=\pm 1$. When $r \gg 1$, polarization lasts for a time that diverges as $r^M \ln N$, where $N$ is the population's size. Finally, an extremist consensus ($k=M$ or $-M$) is reached in a time that scales as $r^{-1}$ for $r \ll 1$

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 $A$ and $B$. The opinion dynamics on network $A$ corresponds to that of the M-model, where the state of each agent can take one of four possible values ($S=-2,-1,1,2$), describing its level of agreement on a given issue. The likelihood to become an extremist ($S=\pm 2$) or a moderate ($S=\pm 1$) is controlled by a reinforcement parameter $r \ge 0$. The decision making dynamics on network $B$ is akin to that of the Abrams-Strogatz model, where agents can be either in favor ($S=+1$) or against ($S=-1$) 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 $\beta$. Starting from a polarized case scenario in which all agents of network $A$ hold positive orientations while all agents of network $B$ 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 $\beta$, the two-network system reaches a consensus in the positive state (initial state of network $A$) when the reinforcement overcomes a crossover value $r^*(\beta)$, while a negative consensus happens for $r<r^*(\beta)$. In the $r-\beta$ phase space, the system displays a transition at a critical threshold $\beta_c$, from a coexistence of both orientations for $\beta<\beta_c$ to a dominance of one orientation for $\beta>\beta_c$. 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 $(r^*,\beta^*)$.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 $q$ of nodes in both networks interact one to one through external connections. We find that as $q$ increases the fluctuations on both networks decrease and thus the synchronization reaches an improvement of nearly $40\%$ when $q=1$. 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 $q$ 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 $\gamma$, that are neighbors of the largest connected component of each constituent network. We find that, for a given initial failure of a fraction $1-p$ 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 $\gamma-p$ 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