1,369 research outputs found
Individualization as driving force of clustering phenomena in humans
One of the most intriguing dynamics in biological systems is the emergence of
clustering, the self-organization into separated agglomerations of individuals.
Several theories have been developed to explain clustering in, for instance,
multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of
fish, and animal herds. A persistent puzzle, however, is clustering of opinions
in human populations. The puzzle is particularly pressing if opinions vary
continuously, such as the degree to which citizens are in favor of or against a
vaccination program. Existing opinion formation models suggest that
"monoculture" is unavoidable in the long run, unless subsets of the population
are perfectly separated from each other. Yet, social diversity is a robust
empirical phenomenon, although perfect separation is hardly possible in an
increasingly connected world. Considering randomness did not overcome the
theoretical shortcomings so far. Small perturbations of individual opinions
trigger social influence cascades that inevitably lead to monoculture, while
larger noise disrupts opinion clusters and results in rampant individualism
without any social structure. Our solution of the puzzle builds on recent
empirical research, combining the integrative tendencies of social influence
with the disintegrative effects of individualization. A key element of the new
computational model is an adaptive kind of noise. We conduct simulation
experiments to demonstrate that with this kind of noise, a third phase besides
individualism and monoculture becomes possible, characterized by the formation
of metastable clusters with diversity between and consensus within clusters.
When clusters are small, individualization tendencies are too weak to prohibit
a fusion of clusters. When clusters grow too large, however, individualization
increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure
Social Influence and the Collective Dynamics of Opinion Formation
Social influence is the process by which individuals adapt their opinion,
revise their beliefs, or change their behavior as a result of social
interactions with other people. In our strongly interconnected society, social
influence plays a prominent role in many self-organized phenomena such as
herding in cultural markets, the spread of ideas and innovations, and the
amplification of fears during epidemics. Yet, the mechanisms of opinion
formation remain poorly understood, and existing physics-based models lack
systematic empirical validation. Here, we report two controlled experiments
showing how participants answering factual questions revise their initial
judgments after being exposed to the opinion and confidence level of others.
Based on the observation of 59 experimental subjects exposed to peer-opinion
for 15 different items, we draw an influence map that describes the strength of
peer influence during interactions. A simple process model derived from our
observations demonstrates how opinions in a group of interacting people can
converge or split over repeated interactions. In particular, we identify two
major attractors of opinion: (i) the expert effect, induced by the presence of
a highly confident individual in the group, and (ii) the majority effect,
caused by the presence of a critical mass of laypeople sharing similar
opinions. Additional simulations reveal the existence of a tipping point at
which one attractor will dominate over the other, driving collective opinion in
a given direction. These findings have implications for understanding the
mechanisms of public opinion formation and managing conflicting situations in
which self-confident and better informed minorities challenge the views of a
large uninformed majority.Comment: Published Nov 05, 2013. Open access at:
http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.007843
Opinion Formation and the Collective Dynamics of Risk Perception
The formation of collective opinion is a complex phenomenon that results from
the combined effects of mass media exposure and social influence between
individuals. The present work introduces a model of opinion formation
specifically designed to address risk judgments, such as attitudes towards
climate change, terrorist threats, or children vaccination. The model assumes
that people collect risk information from the media environment and exchange
them locally with other individuals. Even though individuals are initially
exposed to the same sample of information, the model predicts the emergence of
opinion polarization and clustering. In particular, numerical simulations
highlight two crucial factors that determine the collective outcome: the
propensity of individuals to search for independent information, and the
strength of social influence. This work provides a quantitative framework to
anticipate and manage how the public responds to a given risk, and could help
understanding the systemic amplification of fears and worries, or the
underestimation of real dangers
Social Conformity Despite Individual Preferences for Distinctiveness
We demonstrate that individual behaviors directed at the attainment of
distinctiveness can in fact produce complete social conformity. We thus offer
an unexpected generative mechanism for this central social phenomenon.
Specifically, we establish that agents who have fixed needs to be distinct and
adapt their positions to achieve distinctiveness goals, can nevertheless
self-organize to a limiting state of absolute conformity. This seemingly
paradoxical result is deduced formally from a small number of natural
assumptions, and is then explored at length computationally. Interesting
departures from this conformity equilibrium are also possible, including
divergence in positions. The effect of extremist minorities on these dynamics
is discussed. A simple extension is then introduced, which allows the model to
generate and maintain social diversity, including multimodal distinctiveness
distributions. The paper contributes formal definitions, analytical deductions,
and counterintuitive findings to the literature on individual distinctiveness
and social conformity.Comment: 11 pages, 6 figures, appendi
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
- …