56,731 research outputs found
Validating argument-based opinion dynamics with survey experiments
The empirical validation of models remains one of the most important
challenges in opinion dynamics. In this contribution, we report on recent
developments on combining data from survey experiments with computational
models of opinion formation. We extend previous work on the empirical
assessment of an argument-based model for opinion dynamics in which biased
processing is the principle mechanism. While previous work (Banisch & Shamon,
in press) has focused on calibrating the micro mechanism with experimental data
on argument-induced opinion change, this paper concentrates on the macro level
using the empirical data gathered in the survey experiment. For this purpose,
the argument model is extended by an external source of balanced information
which allows to control for the impact of peer influence processes relative to
other noisy processes. We show that surveyed opinion distributions are matched
with a high level of accuracy in a specific region in the parameter space,
indicating an equal impact of social influence and external noise. More
importantly, the estimated strength of biased processing given the macro data
is compatible with those values that achieve high likelihood at the micro
level. The main contribution of the paper is hence to show that the extended
argument-based model provides a solid bridge from the micro processes of
argument-induced attitude change to macro level opinion distributions. Beyond
that, we review the development of argument-based models and present a new
method for the automated classification of model outcomes.Comment: Keywords: opinion dynamics, validation, empirical confirmation,
survey experiments, parameter estimation, argument communication theory,
computational social scienc
Dynamic Trading and Asset Prices: Keynes vs. Hayek
We investigate the dynamics of prices, information and expectations in a competitive, noisy, dynamic asset pricing equilibrium model with long-term investors. We argue that the fact that prices can score worse or better than consensus opinion in predicting the fundamentals is a product of endogenous short-term speculation. For a given, positive level of residual payoff uncertainty, if noise trade displays low persistence rational investors act like market makers, accommodate the order flow, and prices are farther away from fundamentals compared to consensus. This defines a “Keynesian” region; the complementary region is “Hayekian” in that rational investors chase the trend and prices are systematically closer to fundamentals than average expectations. The standard case of no residual uncertainty and noise trading following a random walk is on the frontier of the two regions and identifies the set of deep parameters for which rational investors abide by Keynes’ dictum of concentrating on an asset “long term prospects and those only.” The analysis explains how accommodation and trend chasing strategies differ from momentum and reversal phenomena because of the different information sets that investors and an outside observer have.efficient market hypothesis, long and short-term trading, average expectations, higher order beliefs, over-reliance on public information, opaqueness, momentum, reversal
The noisy voter model under the influence of contrarians
The influence of contrarians on the noisy voter model is studied at the
mean-field level. The noisy voter model is a variant of the voter model where
agents can adopt two opinions, optimistic or pessimistic, and can change them
by means of an imitation (herding) and an intrinsic (noise) mechanisms. An
ensemble of noisy voters undergoes a finite-size phase transition, upon
increasing the relative importance of the noise to the herding, form a bimodal
phase where most of the agents shear the same opinion to a unimodal phase where
almost the same fraction of agent are in opposite states. By the inclusion of
contrarians we allow for some voters to adopt the opposite opinion of other
agents (anti-herding). We first consider the case of only contrarians and show
that the only possible steady state is the unimodal one. More generally, when
voters and contrarians are present, we show that the bimodal-unimodal
transition of the noisy voter model prevails only if the number of contrarians
in the system is smaller than four, and their characteristic rates are small
enough. For the number of contrarians bigger or equal to four, the voters and
the contrarians can be seen only in the unimodal phase. Moreover, if the number
of voters and contrarians, as well as the noise and herding rates, are of the
same order, then the probability functions of the steady state are very well
approximated by the Gaussian distribution
The noisy Hegselmann-Krause model for opinion dynamics
In the model for continuous opinion dynamics introduced by Hegselmann and
Krause, each individual moves to the average opinion of all individuals within
an area of confidence. In this work we study the effects of noise in this
system. With certain probability, individuals are given the opportunity to
change spontaneously their opinion to another one selected randomly inside the
opinion space with different rules. If the random jump does not occur,
individuals interact through the Hegselmann-Krause's rule. We analyze two
cases, one where individuals can carry out opinion random jumps inside the
whole opinion space, and other where they are allowed to perform jumps just
inside a small interval centered around the current opinion. We found that
these opinion random jumps change the model behavior inducing interesting
phenomena. Using pattern formation techniques, we obtain approximate analytical
results for critical conditions of opinion cluster formation. Finally, we
compare the results of this work with the noisy version of the Deffuant et al.
model for continuous-opinion dynamics
Consensus and diversity in multi-state noisy voter models
We study a variant of the voter model with multiple opinions; individuals can
imitate each other and also change their opinion randomly in mutation events.
We focus on the case of a population with all-to-all interaction. A
noise-driven transition between regimes with multi-modal and unimodal
stationary distributions is observed. In the former, the population is mostly
in consensus states; in the latter opinions are mixed. We derive an effective
death-birth process, describing the dynamics from the perspective of one of the
opinions, and use it to analytically compute marginals of the stationary
distribution. These calculations are exact for models with homogeneous
imitation and mutation rates, and an approximation if rates are heterogeneous.
Our approach can be used to characterize the noise-driven transition and to
obtain mean switching times between consensus states.Comment: 14 pages, 8 figure
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