582 research outputs found
Slightly generalized Generalized Contagion: Unifying simple models of biological and social spreading
We motivate and explore the basic features of generalized contagion, a model
mechanism that unifies fundamental models of biological and social contagion.
Generalized contagion builds on the elementary observation that spreading and
contagion of all kinds involve some form of system memory. We discuss the three
main classes of systems that generalized contagion affords, resembling: simple
biological contagion; critical mass contagion of social phenomena; and an
intermediate, and explosive, vanishing critical mass contagion. We also present
a simple explanation of the global spreading condition in the context of a
small seed of infected individuals.Comment: 8 pages, 5 figures; chapter to appear in "Spreading Dynamics in
Social Systems"; Eds. Sune Lehmann and Yong-Yeol Ahn, Springer Natur
The microfoundations of territorial disputes: Evidence from a survey experiment in Japan
Although territorial disputes are one of the most fraught issues among states, how public opinion on territorial disputes varies within states and what explains the variation are often overlooked. This paper argues that citizens who prioritize economic considerations are more likely to support compromises over such disputes, while those who prioritize a country’s reputation tend to reject any compromise. Further, the paper hypothesizes that such variation in individual preferences can be explained by proximity to disputed territories. Counterintuitively, residents closer to disputes are more likely to support a compromise than those who live further away, because they are more affected by economic considerations. Those far from the disputed territory can afford to focus on its political aspects, which leads to a more hawkish stance. By using an experimental approach within Japan, this paper examines the validity of the spatial argument, and tests the relative salience of economic and political aspects of territorial disputes. The findings, based on original survey data, show that distance from disputed territories shapes individual preferences, and under some conditions, people living further away from disputed territories are more hawkish
A gauge invariant chiral unitary framework for kaon photo- and electroproduction on the proton
We present a gauge invariant approach to photoproduction of mesons on
nucleons within a chiral unitary framework. The interaction kernel for
meson-baryon scattering is derived from the chiral effective Lagrangian and
iterated in a Bethe-Salpeter equation. Within the leading order approximation
to the interaction kernel, data on kaon photoproduction from SAPHIR, CLAS and
CBELSA/TAPS are analyzed in the threshold region. The importance of gauge
invariance and the precision of various approximations in the interaction
kernel utilized in earlier works are discussed.Comment: 23 pages, 13 figs, EPJ A styl
Simulating complex social behaviour with the genetic action tree kernel
The concept of genetic action trees combines action trees with genetic algorithms. In this paper, we create a multi-agent simulation on the base of this concept and provide the interested reader with a software package to apply genetic action trees in a multi-agent simulation to simulate complex social behaviour. An example model is introduced to conduct a feasibility study with the described method. We find that our library can be used to simulate the behaviour of agents in a complex setting and observe a convergence to a global optimum in spite of the absence of stable states
Dynamics of Transformation from Segregation to Mixed Wealth Cities
We model the dynamics of the Schelling model for agents described simply by a
continuously distributed variable - wealth. Agents move to neighborhoods where
their wealth is not lesser than that of some proportion of their neighbors, the
threshold level. As in the case of the classic Schelling model where
segregation obtains between two races, we find here that wealth-based
segregation occurs and persists. However, introducing uncertainty into the
decision to move - that is, with some probability, if agents are allowed to
move even though the threshold level condition is contravened - we find that
even for small proportions of such disallowed moves, the dynamics no longer
yield segregation but instead sharply transition into a persistent mixed wealth
distribution. We investigate the nature of this sharp transformation between
segregated and mixed states, and find that it is because of a non-linear
relationship between allowed moves and disallowed moves. For small increases in
disallowed moves, there is a rapid corresponding increase in allowed moves, but
this tapers off as the fraction of disallowed moves increase further and
finally settles at a stable value, remaining invariant to any further increase
in disallowed moves. It is the overall effect of the dynamics in the initial
region (with small numbers of disallowed moves) that shifts the system away
from a state of segregation rapidly to a mixed wealth state.
The contravention of the tolerance condition could be interpreted as public
policy interventions like minimal levels of social housing or housing benefit
transfers to poorer households. Our finding therefore suggests that it might
require only very limited levels of such public intervention - just sufficient
to enable a small fraction of disallowed moves, because the dynamics generated
by such moves could spur the transformation from a segregated to mixed
equilibrium.Comment: 12 pages, 7 figure
Segregation discovery in a social network of companies
We introduce a framework for a data-driven analysis of segregation
of minority groups in social networks, and challenge it on a complex
scenario. The framework builds on quantitative measures of segregation,
called segregation indexes, proposed in the social science literature.
The segregation discovery problem consists of searching sub-graphs and
sub-groups for which a reference segregation index is above a minimum
threshold. A search algorithm is devised that solves the segregation problem.
The framework is challenged on the analysis of segregation of social
groups in the boards of directors of the real and large network of Italian
companies connected through shared directors
The Naming Game in Social Networks: Community Formation and Consensus Engineering
We study the dynamics of the Naming Game [Baronchelli et al., (2006) J. Stat.
Mech.: Theory Exp. P06014] in empirical social networks. This stylized
agent-based model captures essential features of agreement dynamics in a
network of autonomous agents, corresponding to the development of shared
classification schemes in a network of artificial agents or opinion spreading
and social dynamics in social networks. Our study focuses on the impact that
communities in the underlying social graphs have on the outcome of the
agreement process. We find that networks with strong community structure hinder
the system from reaching global agreement; the evolution of the Naming Game in
these networks maintains clusters of coexisting opinions indefinitely. Further,
we investigate agent-based network strategies to facilitate convergence to
global consensus.Comment: The original publication is available at
http://www.springerlink.com/content/70370l311m1u0ng3
The Emergence of Consensus: a primer
The origin of population-scale coordination has puzzled philosophers and scientists for centuries. Recently, game theory, evolutionary approaches and complex systems science have provided quantitative insights on the mechanisms of social consensus. This paper overviews the main dimensions over which the debate has unfolded and discusses some representative results, with a focus on those situations in which consensus emerges `spontaneously' in absence of centralised institutions. Covered topics include the macroscopic consequences of the different microscopic rules of behavioural contagion, the role of social networks, and the mechanisms that prevent the formation of a consensus or alter it after it has emerged. Special attention is devoted to the recent wave of experiments on the emergence of consensus in social systems
The Epidemics of Donations: Logistic Growth and Power-Laws
This paper demonstrates that collective social dynamics resulting from individual donations can be well described by an epidemic model. It captures the herding behavior in donations as a non-local interaction between individual via a time-dependent mean field representing the mass media. Our study is based on the statistical analysis of a unique dataset obtained before and after the tsunami disaster of 2004. We find a power-law behavior for the distributions of donations with similar exponents for different countries. Even more remarkably, we show that these exponents are the same before and after the tsunami, which accounts for some kind of universal behavior in donations independent of the actual event. We further show that the time-dependent change of both the number and the total amount of donations after the tsunami follows a logistic growth equation. As a new element, a time-dependent scaling factor appears in this equation which accounts for the growing lack of public interest after the disaster. The results of the model are underpinned by the data analysis and thus also allow for a quantification of the media influence
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