5,944 research outputs found
Election results and the Sznajd model on Barabasi network
The network of Barabasi and Albert, a preferential growth model where a new
node is linked to the old ones with a probability proportional to their
connectivity, is applied to Brazilian election results. The application of the
Sznajd rule, that only agreeing pairs of people can convince their neighbours,
gives a vote distribution in good agreement with reality.Comment: 7 pages including two figures, for Eur. Phys. J.
The Sznajd Consensus Model with Continuous Opinions
In the consensus model of Sznajd, opinions are integers and a randomly chosen
pair of neighbouring agents with the same opinion forces all their neighbours
to share that opinion. We propose a simple extension of the model to continuous
opinions, based on the criterion of bounded confidence which is at the basis of
other popular consensus models. Here the opinion s is a real number between 0
and 1, and a parameter \epsilon is introduced such that two agents are
compatible if their opinions differ from each other by less than \epsilon. If
two neighbouring agents are compatible, they take the mean s_m of their
opinions and try to impose this value to their neighbours. We find that if all
neighbours take the average opinion s_m the system reaches complete consensus
for any value of the confidence bound \epsilon. We propose as well a weaker
prescription for the dynamics and discuss the corresponding results.Comment: 11 pages, 4 figures. To appear in International Journal of Modern
Physics
On the Consensus Threshold for the Opinion Dynamics of Krause-Hegselmann
In the consensus model of Krause-Hegselmann, opinions are real numbers
between 0 and 1 and two agents are compatible if the difference of their
opinions is smaller than the confidence bound parameter \epsilon. A randomly
chosen agent takes the average of the opinions of all neighbouring agents which
are compatible with it. We propose a conjecture, based on numerical evidence,
on the value of the consensus threshold \epsilon_c of this model. We claim that
\epsilon_c can take only two possible values, depending on the behaviour of the
average degree d of the graph representing the social relationships, when the
population N goes to infinity: if d diverges when N goes to infinity,
\epsilon_c equals the consensus threshold \epsilon_i ~ 0.2 on the complete
graph; if instead d stays finite when N goes to infinity, \epsilon_c=1/2 as for
the model of Deffuant et al.Comment: 15 pages, 7 figures, to appear in International Journal of Modern
Physics C 16, issue 2 (2005
The Krause-Hegselmann Consensus Model with Discrete Opinions
The consensus model of Krause and Hegselmann can be naturally extended to the
case in which opinions are integer instead of real numbers. Our algorithm is
much faster than the original version and thus more suitable for applications.
For the case of a society in which everybody can talk to everybody else, we
find that the chance to reach consensus is much higher as compared to other
models; if the number of possible opinions Q<=7, in fact, consensus is always
reached, which might explain the stability of political coalitions with more
than three or four parties. For Q>7 the number S of surviving opinions is
approximately the same independently of the size N of the population, as long
as Q<N. We considered as well the more realistic case of a society structured
like a Barabasi-Albert network; here the consensus threshold depends on the
outdegree of the nodes and we find a simple scaling law for S, as observed for
the discretized Deffuant model.Comment: 12 pages, 6 figure
The Spread of Opinions and Proportional Voting
Election results are determined by numerous social factors that affect the
formation of opinion of the voters, including the network of interactions
between them and the dynamics of opinion influence. In this work we study the
result of proportional elections using an opinion dynamics model similar to
simple opinion spreading over a complex network. Erdos-Renyi, Barabasi-Albert,
regular lattices and randomly augmented lattices are considered as models of
the underlying social networks. The model reproduces the power law behavior of
number of candidates with a given number of votes found in real elections with
the correct slope, a cutoff for larger number of votes and a plateau for small
number of votes. It is found that the small world property of the underlying
network is fundamental for the emergence of the power law regime.Comment: 10 pages, 7 figure
Emergence of Hierarchy on a Network of Complementary Agents
Complementarity is one of the main features underlying the interactions in
biological and biochemical systems. Inspired by those systems we propose a
model for the dynamical evolution of a system composed by agents that interact
due to their complementary attributes rather than their similarities. Each
agent is represented by a bit-string and has an activity associated to it; the
coupling among complementary peers depends on their activity. The connectivity
of the system changes in time respecting the constraint of complementarity. We
observe the formation of a network of active agents whose stability depends on
the rate at which activity diffuses in the system. The model exhibits a
non-equilibrium phase transition between the ordered phase, where a stable
network is generated, and a disordered phase characterized by the absence of
correlation among the agents. The ordered phase exhibits multi-modal
distributions of connectivity and activity, indicating a hierarchy of
interaction among different populations characterized by different degrees of
activity. This model may be used to study the hierarchy observed in social
organizations as well as in business and other networks.Comment: 13 pages, 4 figures, submitte
Plurality Voting: the statistical laws of democracy in Brazil
We explore the statistical laws behind the plurality voting system by
investigating the election results for mayor held in Brazil in 2004. Our
analysis indicate that the vote partition among mayor candidates of the same
city tends to be "polarized" between two candidates, a phenomenon that can be
closely described by means of a simple fragmentation model. Complex concepts
like "government continuity" and "useful vote" can be identified and even
statistically quantified through our approach.Comment: 4 pages, 4 figure
Immunization and Aging: a Learning Process in the Immune Network
The immune system can be thought as a complex network of different
interacting elements. A cellular automaton, defined in shape-space, was
recently shown to exhibit self-regulation and complex behavior and is,
therefore, a good candidate to model the immune system. Using this model to
simulate a real immune system we find good agreement with recent experiments on
mice. The model exhibits the experimentally observed refractory behavior of the
immune system under multiple antigen presentations as well as loss of its
plasticity caused by aging.Comment: 4 latex pages, 3 postscript figures attached. To be published in
Physical Review Letters (Tentatively scheduled for 5th Oct. issue
Medida de desumanização baseada em traços: adaptação para a população Portuguesa
Although dehumanization (i.e., the denial of full humanness to others; Haslam, 2006) has been a frequent subject in social psychology, a set of traits designed to evaluate this phenomenon has not been validated to the Portuguese population. The main purpose of this study was to translate, culturally adapt and validate a set of dehumanization traits proposed by Haslam and colleagues (Haslam & Bain, 2007; Haslam, Bain, Douge, Lee & Bastian, 2005), which measure both the denial of uniquely human and human nature traits. A sample of 597 individuals (Mage = 40.83; SD = 11.50) were asked to rate a set of 52 traits on how much they perceived each as a characteristic of human nature and human uniqueness, as well as its desirability. T-tests were conducted to distinguish between low and high rated traits in each dimension, and to construct clusters of traits that differ in each dimension. We successfully provide a measure containing positive traits in both senses of humanness dimensions; however, we were only able to validate a human uniqueness measure with negative valence. Implications of this measure for future research on dehumanization processes are discussed.info:eu-repo/semantics/publishedVersio
On Spatial Consensus Formation: Is the Sznajd Model Different from a Voter Model?
In this paper, we investigate the so-called ``Sznajd Model'' (SM) in one
dimension, which is a simple cellular automata approach to consensus formation
among two opposite opinions (described by spin up or down). To elucidate the SM
dynamics, we first provide results of computer simulations for the
spatio-temporal evolution of the opinion distribution , the evolution of
magnetization , the distribution of decision times and
relaxation times . In the main part of the paper, it is shown that the
SM can be completely reformulated in terms of a linear VM, where the transition
rates towards a given opinion are directly proportional to frequency of the
respective opinion of the second-nearest neighbors (no matter what the nearest
neighbors are). So, the SM dynamics can be reduced to one rule, ``Just follow
your second-nearest neighbor''. The equivalence is demonstrated by extensive
computer simulations that show the same behavior between SM and VM in terms of
, , , , and the final attractor statistics. The
reformulation of the SM in terms of a VM involves a new parameter , to
bias between anti- and ferromagnetic decisions in the case of frustration. We
show that plays a crucial role in explaining the phase transition
observed in SM. We further explore the role of synchronous versus asynchronous
update rules on the intermediate dynamics and the final attractors. Compared to
the original SM, we find three additional attractors, two of them related to an
asymmetric coexistence between the opposite opinions.Comment: 22 pages, 20 figures. For related publications see
http://www.ais.fraunhofer.de/~fran
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