153 research outputs found
Continuous Opinions and Discrete Actions in Opinion Dynamics Problems
A model where agents show discrete behavior regarding their actions, but have
continuous opinions that are updated by interacting with other agents is
presented. This new updating rule is applied to both the voter and Sznajd
models for interaction between neighbors and its consequences are discussed.
The appearance of extremists is naturally observed and it seems to be a
characteristic of this model.Comment: 10 pages, 4 figures, minor changes for improved clarit
Bayesian Updating Rules in Continuous Opinion Dynamics Models
In this article, I investigate the use of Bayesian updating rules applied to
modeling social agents in the case of continuos opinions models. Given another
agent statement about the continuous value of a variable , we will see that
interesting dynamics emerge when an agent assigns a likelihood to that value
that is a mixture of a Gaussian and a Uniform distribution. This represents the
idea the other agent might have no idea about what he is talking about. The
effect of updating only the first moments of the distribution will be studied.
and we will see that this generates results similar to those of the Bounded
Confidence models. By also updating the second moment, several different
opinions always survive in the long run. However, depending on the probability
of error and initial uncertainty, those opinions might be clustered around a
central value.Comment: 14 pages, 5 figures, presented at SigmaPhi200
Nonequilibrium phase transition in the coevolution of networks and opinions
Models of the convergence of opinion in social systems have been the subject
of a considerable amount of recent attention in the physics literature. These
models divide into two classes, those in which individuals form their beliefs
based on the opinions of their neighbors in a social network of personal
acquaintances, and those in which, conversely, network connections form between
individuals of similar beliefs. While both of these processes can give rise to
realistic levels of agreement between acquaintances, practical experience
suggests that opinion formation in the real world is not a result of one
process or the other, but a combination of the two. Here we present a simple
model of this combination, with a single parameter controlling the balance of
the two processes. We find that the model undergoes a continuous phase
transition as this parameter is varied, from a regime in which opinions are
arbitrarily diverse to one in which most individuals hold the same opinion. We
characterize the static and dynamical properties of this transition
Effects of noise and confidence thresholds in nominal and metric Axelrod dynamics of social influence
We study the effects of bounded confidence thresholds and of interaction and
external noise on Axelrod's model of social influence. Our study is based on a
combination of numerical simulations and an integration of the mean-field
Master equation describing the system in the thermodynamic limit. We find that
interaction thresholds affect the system only quantitatively, but that they do
not alter the basic phase structure. The known crossover between an ordered and
a disordered state in finite systems subject to external noise persists in
models with general confidence threshold. Interaction noise here facilitates
the dynamics and reduces relaxation times. We also study Axelrod systems with
metric features, and point out similarities and differences compared to models
with nominal features. Metric features are used to demonstrate that a small
group of extremists can have a significant impact on the opinion dynamics of a
population of Axelrod agents.Comment: 15 pages, 12 figure
Dynamic scaling regimes of collective decision making
We investigate a social system of agents faced with a binary choice. We
assume there is a correct, or beneficial, outcome of this choice. Furthermore,
we assume agents are influenced by others in making their decision, and that
the agents can obtain information that may guide them towards making a correct
decision. The dynamic model we propose is of nonequilibrium type, converging to
a final decision. We run it on random graphs and scale-free networks. On random
graphs, we find two distinct regions in terms of the "finalizing time" -- the
time until all agents have finalized their decisions. On scale-free networks on
the other hand, there does not seem to be any such distinct scaling regions
Social Effects in Science: Modelling Agents for a Better Scientific Practice
Science is a fundamental human activity and we trust its results because it
has several error-correcting mechanisms. Its is subject to experimental tests
that are replicated by independent parts. Given the huge amount of information
available, scientists have to rely on the reports of others. This makes it
possible for social effects to influence the scientific community. Here, an
Opinion Dynamics agent model is proposed to describe this situation. The
influence of Nature through experiments is described as an external field that
acts on the experimental agents. We will see that the retirement of old
scientists can be fundamental in the acceptance of a new theory. We will also
investigate the interplay between social influence and observations. This will
allow us to gain insight in the problem of when social effects can have
negligible effects in the conclusions of a scientific community and when we
should worry about them.Comment: 14 pages, 5 figure
Mobility and Social Network Effects on Extremist Opinions
Understanding the emergence of extreme opinions and in what kind of
environment they might become less extreme is a central theme in our modern
globalized society. A model combining continuous opinions and observed discrete
actions (CODA) capable of addressing the important issue of measuring how
extreme opinions might be has been recently proposed. In this paper I show
extreme opinions to arise in a ubiquitous manner in the CODA model for a
multitude of social network structures. Depending on network details reducing
extremism seems to be possible. However, a large number agents with extreme
opinions is always observed. A significant decrease in the number of extremists
can be observed by allowing agents to change their positions in the network.Comment: 7 pages, 8 figures, discussion expanded, new references, new figure
Rise of the centrist: from binary to continuous opinion dynamics
We propose a model that extends the binary ``united we stand, divided we
fall'' opinion dynamics of Sznajd-Weron to handle continuous and multi-state
discrete opinions. Disagreement dynamics are often ignored in continuous
extensions of the binary rules, so we make the most symmetric continuum
extension of the binary model that can treat the consequences of agreement
(debate) and disagreement (confrontation) within a population of agents. We use
the continuum extension as an opportunity to develop rules for persistence of
opinion (memory). Rules governing the propagation of centrist views are also
examined. Monte Carlo simulations are carried out. We find that both memory
effects and the type of centrist significantly modify the variance of average
opinions in the large timescale limits of the models. Finally, we describe the
limit of applicability for Sznajd-Weron's model of binary opinions as the
continuum limit is approached. By comparing Monte Carlo results and long
time-step limits, we find that the opinion dynamics of binary models are
significantly different to those where agents are permitted more than 3
opinions
Universality in movie rating distributions
In this paper histograms of user ratings for movies (1,...,10) are analysed.
The evolving stabilised shapes of histograms follow the rule that all are
either double- or triple-peaked. Moreover, at most one peak can be on the
central bins 2,...,9 and the distribution in these bins looks smooth
`Gaussian-like' while changes at the extremes (1 and 10) often look abrupt. It
is shown that this is well approximated under the assumption that histograms
are confined and discretised probability density functions of L\'evy skew
alpha-stable distributions. These distributions are the only stable
distributions which could emerge due to a generalized central limit theorem
from averaging of various independent random avriables as which one can see the
initial opinions of users. Averaging is also an appropriate assumption about
the social process which underlies the process of continuous opinion formation.
Surprisingly, not the normal distribution achieves the best fit over histograms
obseved on the web, but distributions with fat tails which decay as power-laws
with exponent -(1+alpha) (alpha=4/3). The scale and skewness parameters of the
Levy skew alpha-stable distributions seem to depend on the deviation from an
average movie (with mean about 7.6). The histogram of such an average movie has
no skewness and is the most narrow one. If a movie deviates from average the
distribution gets broader and skew. The skewness pronounces the deviation. This
is used to construct a one parameter fit which gives some evidence of
universality in processes of continuous opinion dynamics about taste.Comment: 8 pages, 5 figures, accepted for publicatio
The role of noise and initial conditions in the asymptotic solution of a bounded confidence, continuous-opinion model
We study a model for continuous-opinion dynamics under bounded confidence. In
particular, we analyze the importance of the initial distribution of opinions
in determining the asymptotic configuration. Thus, we sketch the structure of
attractors of the dynamical system, by means of the numerical computation of
the time evolution of the agents density. We show that, for a given bound of
confidence, a consensus can be encouraged or prevented by certain initial
conditions. Furthermore, a noisy perturbation is added to the system with the
purpose of modeling the free will of the agents. As a consequence, the
importance of the initial condition is partially replaced by that of the
statistical distribution of the noise. Nevertheless, we still find evidence of
the influence of the initial state upon the final configuration for a short
range of the bound of confidence parameter
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