132 research outputs found
System size stochastic resonance in a model for opinion formation
We study a model for opinion formation which incorporates three basic
ingredients for the evolution of the opinion held by an individual: imitation,
influence of fashion and randomness. We show that in the absence of fashion,
the model behaves as a bistable system with random jumps between the two stable
states with a distribution of times following Kramer's law. We also demonstrate
the existence of system size stochastic resonance, by which there is an optimal
value for the number of individuals N for which the average opinion follows
better the fashion.Comment: 10 pages, to appear in Physica
Synchronised firing induced by network dynamics in excitable systems
We study the collective dynamics of an ensemble of coupled identical
FitzHugh--Nagumo elements in their excitable regime. We show that collective
firing, where all the elements perform their individual firing cycle
synchronously, can be induced by random changes in the interaction pattern.
Specifically, on a sparse evolving network where, at any time, each element is
connected with at most one partner, collective firing occurs for intermediate
values of the rewiring frequency. Thus, network dynamics can replace noise and
connectivity in inducing this kind of self-organised behaviour in highly
disconnected systems which, otherwise, wouldn't allow for the spreading of
coherent evolution.Comment: 5 pages, 5 figure
Quantifying the effects of social influence
How do humans respond to indirect social influence when making decisions? We
analysed an experiment where subjects had to repeatedly guess the correct
answer to factual questions, while having only aggregated information about the
answers of others. While the response of humans to aggregated information is a
widely observed phenomenon, it has not been investigated quantitatively, in a
controlled setting. We found that the adjustment of individual guesses depends
linearly on the distance to the mean of all guesses. This is a remarkable, and
yet surprisingly simple, statistical regularity. It holds across all questions
analysed, even though the correct answers differ in several orders of
magnitude. Our finding supports the assumption that individual diversity does
not affect the response to indirect social influence. It also complements
previous results on the nonlinear response in information-rich scenarios. We
argue that the nature of the response to social influence crucially changes
with the level of information aggregation. This insight contributes to the
empirical foundation of models for collective decisions under social influence.Comment: 3 figure
Hierarchical Consensus Formation Reduces the Influence of Opinion Bias
We study the role of hierarchical structures in a simple model of collective
consensus formation based on the bounded confidence model with continuous
individual opinions. For the particular variation of this model considered in
this paper, we assume that a bias towards an extreme opinion is introduced
whenever two individuals interact and form a common decision. As a simple proxy
for hierarchical social structures, we introduce a two-step decision making
process in which in the second step groups of like-minded individuals are
replaced by representatives once they have reached local consensus, and the
representatives in turn form a collective decision in a downstream process. We
find that the introduction of such a hierarchical decision making structure can
improve consensus formation, in the sense that the eventual collective opinion
is closer to the true average of individual opinions than without it. In
particular, we numerically study how the size of groups of like-minded
individuals being represented by delegate individuals affects the impact of the
bias on the final population-wide consensus. These results are of interest for
the design of organisational policies and the optimisation of hierarchical
structures in the context of group decision making.Comment: 12 pages, 5 figure
Diversity-induced resonance
We present conclusive evidence showing that different sources of diversity,
such as those represented by quenched disorder or noise, can induce a resonant
collective behavior in an ensemble of coupled bistable or excitable systems.
Our analytical and numerical results show that when such systems are subjected
to an external subthreshold signal, their response is optimized for an
intermediate value of the diversity. These findings show that intrinsic
diversity might have a constructive role and suggest that natural systems might
profit from their diversity in order to optimize the response to an external
stimulus.Comment: 4 pages, 3 figure
Antagonistic Structural Patterns in Complex Networks
Identifying and explaining the structure of complex networks at different
scales has become an important problem across disciplines. At the mesoscale,
modular architecture has attracted most of the attention. At the macroscale,
other arrangements --e.g. nestedness or core-periphery-- have been studied in
parallel, but to a much lesser extent. However, empirical evidence increasingly
suggests that characterizing a network with a unique pattern typology may be
too simplistic, since a system can integrate properties from distinct
organizations at different scales. Here, we explore the relationship between
some of those organizational patterns: two at the mesoscale (modularity and
in-block nestedness); and one at the macroscale (nestedness). We analytically
show that nestedness can be used to provide approximate bounds for modularity,
with exact results in an idealized scenario. Specifically, we show that
nestedness and modularity are antagonistic. Furthermore, we evince that
in-block nestedness provides a parsimonious transition between nested and
modular networks, taking properties of both. Far from a mere theoretical
exercise, understanding the boundaries that discriminate each architecture is
fundamental, to the extent modularity and nestedness are known to place heavy
constraints on the stability of several dynamical processes, specially in
ecology.Comment: 7 pages, 4 figures and 1 supplemental information fil
Network Evolution Based on Centrality
We study the evolution of networks when the creation and decay of links are
based on the position of nodes in the network measured by their centrality. We
show that the same network dynamics arises under various centrality measures,
and solve analytically the network evolution. During the complete evolution,
the network is characterized by nestedness: the neighbourhood of a node is
contained in the neighbourhood of the nodes with larger degree. We find a
discontinuous transition in the network density between hierarchical and
homogeneous networks, depending on the rate of link decay. We also show that
this evolution mechanism leads to double power-law degree distributions, with
interrelated exponents.Comment: 6 pages, 3 figure
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