7,047 research outputs found

    The influence of persuasion in opinion formation and polarization

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    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 kk that expresses its level of agreement on a given issue, from totally against k=Mk=-M to totally in favor k=Mk=M. Same-orientation agents persuade each other with probability pp, becoming more extreme, while opposite-orientation agents become more moderate as they reach a compromise with probability qq. The population initially evolves to (a) a polarized state for r=p/q>1r=p/q>1, where opinions' distribution is peaked at the extreme values k=±Mk=\pm M, or (b) a centralized state for r<1r<1, with most opinions around k=±1k=\pm 1. When r1r \gg 1, polarization lasts for a time that diverges as rMlnNr^M \ln N, where NN is the population's size. Finally, an extremist consensus (k=Mk=M or M-M) is reached in a time that scales as r1r^{-1} for r1r \ll 1

    Fluctuations of a surface relaxation model in interacting scale free networks

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    Isolated complex networks have been studied deeply in the last decades due to the fact that many real systems can be modeled using these types of structures. However, it is well known that the behavior of a system not only depends on itself, but usually also depends on the dynamics of other structures. For this reason, interacting complex networks and the processes developed on them have been the focus of study of many researches in the last years. One of the most studied subjects in this type of structures is the Synchronization problem, which is important in a wide variety of processes in real systems. In this manuscript we study the synchronization of two interacting scale-free networks, in which each node has keke dependency links with different nodes in the other network. We map the synchronization problem with an interface growth, by studying the fluctuations in the steady state of a scalar field defined in both networks. We find that as keke slightly increases from ke=0ke=0, there is a really significant decreasing in the fluctuations of the system. However, this considerable improvement takes place mainly for small values of keke, when the interaction between networks becomes stronger there is only a slight change in the fluctuations. We characterize how the dispersion of the scalar field depends on the internal degree, and we show that a combination between the decreasing of this dispersion and the integer nature of our growth model are the responsible for the behavior of the fluctuations with keke.Comment: 11 pages, 4 figures and 1 tabl

    Interacting social processes on interconnected networks

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    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 AA and BB. The opinion dynamics on network AA corresponds to that of the M-model, where the state of each agent can take one of four possible values (S=2,1,1,2S=-2,-1,1,2), describing its level of agreement on a given issue. The likelihood to become an extremist (S=±2S=\pm 2) or a moderate (S=±1S=\pm 1) is controlled by a reinforcement parameter r0r \ge 0. The decision making dynamics on network BB is akin to that of the Abrams-Strogatz model, where agents can be either in favor (S=+1S=+1) or against (S=1S=-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 β\beta. Starting from a polarized case scenario in which all agents of network AA hold positive orientations while all agents of network BB 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 β\beta, the two-network system reaches a consensus in the positive state (initial state of network AA) when the reinforcement overcomes a crossover value r(β)r^*(\beta), while a negative consensus happens for r<r(β)r<r^*(\beta). In the rβr-\beta phase space, the system displays a transition at a critical threshold βc\beta_c, from a coexistence of both orientations for β<βc\beta<\beta_c to a dominance of one orientation for β>βc\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,β)(r^*,\beta^*).Comment: 25 pages, 6 figure
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