477 research outputs found
Simulation of Consensus Model of Deffuant et al on a Barabasi-Albert Network
In the consensus model with bounded confidence, studied by Deffuant et al.
(2000), two randomly selected people who differ not too much in their opinion
both shift their opinions towards each other. Now we restrict this exchange of
information to people connected by a scale-free network. As a result, the
number of different final opinions (when no complete consensus is formed) is
proportional to the number of people.Comment: 7 pages including 3 figs; Int.J.MOd.Phys.C 15, issue 2; programming
error correcte
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
Monte Carlo Simulation of Deffuant opinion dynamics with quality differences
In this work the consequences of different opinion qualities in the Deffuant
model were examined. If these qualities are randomly distributed, no different
behavior was observed. In contrast to that, systematically assigned qualities
had strong effects to the final opinion distribution. There was a high
probability that the strongest opinion was one with a high quality.
Furthermore, under the same conditions, this major opinion was much stronger
than in the models without systematic differences. Finally, a society with
systematic quality differences needed more tolerance to form a complete
consensus than one without or with unsystematic ones.Comment: 8 pages including 5 space-consuming figures, fir Int. J. Mod. Phys. C
15/1
Universality of the Threshold for Complete Consensus for the Opinion Dynamics of Deffuant et al
In the compromise model of Deffuant et al., 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. The opinions of a
randomly chosen pair of compatible agents get closer to each other. We provide
strong numerical evidence that the threshold value of \epsilon above which all
agents share the same opinion in the final configuration is 1/2, independently
of the underlying social topology.Comment: 8 pages, 4 figures, to appear in Int. J. Mod. Phys. C 15, issue
Opinion formation models based on game theory
A way to simulate the basic interactions between two individuals with
different opinions, in the context of strategic game theory, is proposed.
Various games are considered, which produce different kinds of opinion
formation dynamics. First, by assuming that all individuals (players) are
equals, we obtain the bounded confidence model of continuous opinion dynamics
proposed by Deffuant et al. In such a model a tolerance threshold is defined,
such that individuals with difference in opinion larger than the threshold can
not interact. Then, we consider that the individuals have different
inclinations to change opinion and different abilities in convincing the
others. In this way, we obtain the so-called ``Stubborn individuals and
Orators'' (SO) model, a generalization of the Deffuant et al. model, in which
the threshold tolerance is different for every couple of individuals. We
explore, by numerical simulations, the dynamics of the SO model, and we propose
further generalizations that can be implemented.Comment: 18 pages, 4 figure
Molecular Model of Dynamic Social Network Based on E-mail communication
In this work we consider an application of physically inspired sociodynamical model to the modelling of the evolution of email-based social network. Contrary to the standard approach of sociodynamics, which assumes expressing of system dynamics with heuristically defined simple rules, we postulate the inference of these rules from the real data and their application within a dynamic molecular model. We present how to embed the n-dimensional social space in Euclidean one. Then, inspired by the Lennard-Jones potential, we define a data-driven social potential function and apply the resultant force to a real e-mail communication network in a course of a molecular simulation, with network nodes taking on the role of interacting particles. We discuss all steps of the modelling process, from data preparation, through embedding and the molecular simulation itself, to transformation from the embedding space back to a graph structure. The conclusions, drawn from examining the resultant networks in stable, minimum-energy states, emphasize the role of the embedding process projecting the non–metric social graph into the Euclidean space, the significance of the unavoidable loss of information connected with this procedure and the resultant preservation of global rather than local properties of the initial network. We also argue applicability of our method to some classes of problems, while also signalling the areas which require further research in order to expand this applicability domain
Dynamics of Majority Rule
We introduce a 2-state opinion dynamics model where agents evolve by majority
rule. In each update, a group of agents is specified whose members then all
adopt the local majority state. In the mean-field limit, where a group consists
of randomly-selected agents, consensus is reached in a time that scales ln N,
where N is the number of agents. On finite-dimensional lattices, where a group
is a contiguous cluster, the consensus time fluctuates strongly between
realizations and grows as a dimension-dependent power of N. The upper critical
dimension appears to be larger than 4. The final opinion always equals that of
the initial majority except in one dimension.Comment: 4 pages, 3 figures, 2-column revtex4 format; annoying typo fixed in
Eq.(1); a similar typo fixed in Eq.(6) and some references update
Volatility clustering and scaling for financial time series due to attractor bubbling
A microscopic model of financial markets is considered, consisting of many
interacting agents (spins) with global coupling and discrete-time thermal bath
dynamics, similar to random Ising systems. The interactions between agents
change randomly in time. In the thermodynamic limit the obtained time series of
price returns show chaotic bursts resulting from the emergence of attractor
bubbling or on-off intermittency, resembling the empirical financial time
series with volatility clustering. For a proper choice of the model parameters
the probability distributions of returns exhibit power-law tails with scaling
exponents close to the empirical ones.Comment: For related publications see http://www.helbing.or
Effects of Mass Media and Cultural Drift in a Model for Social Influence
In the context of an extension of Axelrod's model for social influence, we
study the interplay and competition between the cultural drift, represented as
random perturbations, and mass media, introduced by means of an external
homogeneous field. Unlike previous studies [J. C. Gonz\'alez-Avella {\it et
al}, Phys. Rev. E {\bf 72}, 065102(R) (2005)], the mass media coupling proposed
here is capable of affecting the cultural traits of any individual in the
society, including those who do not share any features with the external
message. A noise-driven transition is found: for large noise rates, both the
ordered (culturally polarized) phase and the disordered (culturally fragmented)
phase are observed, while, for lower noise rates, the ordered phase prevails.
In the former case, the external field is found to induce cultural ordering, a
behavior opposite to that reported in previous studies using a different
prescription for the mass media interaction. We compare the predictions of this
model to statistical data measuring the impact of a mass media vasectomy
promotion campaign in Brazil.Comment: 10 pages, 3 figures; minor changes; added references. To appear in
IJMP
Non-equilibrium phase transition in negotiation dynamics
We introduce a model of negotiation dynamics whose aim is that of mimicking
the mechanisms leading to opinion and convention formation in a population of
individuals. The negotiation process, as opposed to ``herding-like'' or
``bounded confidence'' driven processes, is based on a microscopic dynamics
where memory and feedback play a central role. Our model displays a
non-equilibrium phase transition from an absorbing state in which all agents
reach a consensus to an active stationary state characterized either by
polarization or fragmentation in clusters of agents with different opinions. We
show the exystence of at least two different universality classes, one for the
case with two possible opinions and one for the case with an unlimited number
of opinions. The phase transition is studied analytically and numerically for
various topologies of the agents' interaction network. In both cases the
universality classes do not seem to depend on the specific interaction
topology, the only relevant feature being the total number of different
opinions ever present in the system.Comment: 4 pages, 4 figure
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