203,049 research outputs found
Opinion dynamics: models, extensions and external effects
Recently, social phenomena have received a lot of attention not only from
social scientists, but also from physicists, mathematicians and computer
scientists, in the emerging interdisciplinary field of complex system science.
Opinion dynamics is one of the processes studied, since opinions are the
drivers of human behaviour, and play a crucial role in many global challenges
that our complex world and societies are facing: global financial crises,
global pandemics, growth of cities, urbanisation and migration patterns, and
last but not least important, climate change and environmental sustainability
and protection. Opinion formation is a complex process affected by the
interplay of different elements, including the individual predisposition, the
influence of positive and negative peer interaction (social networks playing a
crucial role in this respect), the information each individual is exposed to,
and many others. Several models inspired from those in use in physics have been
developed to encompass many of these elements, and to allow for the
identification of the mechanisms involved in the opinion formation process and
the understanding of their role, with the practical aim of simulating opinion
formation and spreading under various conditions. These modelling schemes range
from binary simple models such as the voter model, to multi-dimensional
continuous approaches. Here, we provide a review of recent methods, focusing on
models employing both peer interaction and external information, and
emphasising the role that less studied mechanisms, such as disagreement, has in
driving the opinion dynamics. [...]Comment: 42 pages, 6 figure
Coordination of Decisions in a Spatial Agent Model
For a binary choice problem, the spatial coordination of decisions in an
agent community is investigated both analytically and by means of stochastic
computer simulations. The individual decisions are based on different local
information generated by the agents with a finite lifetime and disseminated in
the system with a finite velocity. We derive critical parameters for the
emergence of minorities and majorities of agents making opposite decisions and
investigate their spatial organization. We find that dependent on two essential
parameters describing the local impact and the spatial dissemination of
information, either a definite stable minority/majority relation
(single-attractor regime) or a broad range of possible values (multi-attractor
regime) occurs. In the latter case, the outcome of the decision process becomes
rather diverse and hard to predict, both with respect to the share of the
majority and their spatial distribution. We further investigate how a
dissemination of information on different time scales affects the outcome of
the decision process. We find that a more ``efficient'' information exchange
within a subpopulation provides a suitable way to stabilize their majority
status and to reduce ``diversity'' and uncertainty in the decision process.Comment: submitted for publication in Physica A (31 pages incl. 17 multi-part
figures
Consensus Emerging from the Bottom-up: the Role of Cognitive Variables in Opinion Dynamics
The study of opinions e.g., their formation and change, and their effects
on our society by means of theoretical and numerical models has been one of
the main goals of sociophysics until now, but it is one of the defining topics
addressed by social psychology and complexity science. Despite the flourishing
of different models and theories, several key questions still remain
unanswered. The aim of this paper is to provide a cognitively grounded
computational model of opinions in which they are described as mental
representations and defined in terms of distinctive mental features. We also
define how these representations change dynamically through different
processes, describing the interplay between mental and social dynamics of
opinions. We present two versions of the model, one with discrete opinions
(voter model-like), and one with continuous ones (Deffuant-like). By means of
numerical simulations, we compare the behaviour of our cognitive model with the
classical sociophysical models, and we identify interesting differences in the
dynamics of consensus for each of the models considered.Comment: 14 pages, 8 figure
Modelling Collective Opinion Formation by Means of Active Brownian Particles
The concept of active Brownian particles is used to model a collective
opinion formation process. It is assumed that individuals in community create a
two-component communication field that influences the change of opinions of
other persons and/or can induce their migration. The communication field is
described by a reaction-diffusion equation, the opinion change of the
individuals is given by a master equation, while the migration is described by
a set of Langevin equations, coupled by the communication field. In the
mean-field limit holding for fast communication we derive a critical population
size, above which the community separates into a majority and a minority with
opposite opinions. The existence of external support (e.g. from mass media)
changes the ratio between minority and majority, until above a critical
external support the supported subpopulation exists always as a majority.
Spatial effects lead to two critical ``social'' temperatures, between which the
community exists in a metastable state, thus fluctuations below a certain
critical wave number may result in a spatial opinion separation. The range of
metastability is particularly determined by a parameter characterizing the
individual response to the communication field. In our discussion, we draw
analogies to phase transitions in physical systems.Comment: Revised text version. Accepted for publication in European Physics
Journal B. For related work see
http://summa.physik.hu-berlin.de/~frank/active.html and
http://www.if.pw.edu.pl/~jholys
Opinion Polarization by Learning from Social Feedback
We explore a new mechanism to explain polarization phenomena in opinion
dynamics in which agents evaluate alternative views on the basis of the social
feedback obtained on expressing them. High support of the favored opinion in
the social environment, is treated as a positive feedback which reinforces the
value associated to this opinion. In connected networks of sufficiently high
modularity, different groups of agents can form strong convictions of competing
opinions. Linking the social feedback process to standard equilibrium concepts
we analytically characterize sufficient conditions for the stability of
bi-polarization. While previous models have emphasized the polarization effects
of deliberative argument-based communication, our model highlights an affective
experience-based route to polarization, without assumptions about negative
influence or bounded confidence.Comment: Presented at the Social Simulation Conference (Dublin 2017
- …