Minorities in a model for opinion formation

Laguna, María Fabiana; Abramson, Guillermo; Zanette, Damián H.

doi:10.1002/cplx.20018

Cited by 46 publications

(44 citation statements)

References 8 publications

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“…Low µ leads to longer convergence time. But in (42) it is shown by simulation that lower µ also reduces the sizes of the minor clusters. So more cautious agents are not that likely to produce minor clusters.…”

Section: Social Network and Communication Regimesmentioning

confidence: 93%

Continuous Opinion Dynamics Under Bounded Confidence: A Survey

Lorenz

2007

Int. J. Mod. Phys. C

605

546

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Models of continuous opinion dynamics under bounded confidence have been presented independently by Krause and Hegselmann and by Deffuant et al in 2000. They have raised a fair amount of attention in the communities of social simulation, sociophysics and complexity science. The researchers working on it come from disciplines as physics, mathematics, computer science, social psychology and philosophy.In these models agents hold continuous opinions which they can gradually adjust if they hear the opinions of others. The idea of bounded confidence is that agents only interact if they are close in opinion to each other. Usually, the models are analyzed with agent-based simulations in a Monte-Carlo style, but they can also be reformulated on the agent's density in the opinion space in a master-equation style. The contribution of this survey is fourfold. First, it will present the agent-based and density-based modeling frameworks including the cases of multidimensional opinions and heterogeneous bounds of confidence. Second, it will give the bifurcation diagrams of cluster configuration in the homogeneous model with uniformly distributed initial opinions. Third, it will review the several extensions and the evolving phenomena which have been studied so far, and fourth it will state some open questions.

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Section: Social Network and Communication Regimesmentioning

confidence: 93%

Continuous Opinion Dynamics Under Bounded Confidence: A Survey

Lorenz

2007

Int. J. Mod. Phys. C

605

546

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“…The convergence parameter µ of the original model [4,5] is neglected to not further increase the complexity. In [4,5] it has been argued that µ effects only convergence time, later it has been shown that the parameter also impacts the sizes of minority clusters [12] or might get very important under other extensions [8]. Figure 1 shows an example for the DW model in which 500 of 1000 agents are closed-minded (ε 1 = 0.11), the other half open-minded (ε 2 = 0.22).…”

Section: Dw and Hk Model Extended To Heterogeneous Bounds Of Confidencementioning

confidence: 99%

Heterogeneous bounds of confidence: Meet, discuss and find consensus!

Lorenz¹

2009

Complexity

137

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Models of continuous opinion dynamics under bounded confidence show a sharp transition between a consensus and a polarization phase at a critical global bound of confidence. In this paper, heterogeneous bounds of confidence are studied. The surprising result is that a society of agents with two different bounds of confidence (open-minded and closedminded agents) can find consensus even when both bounds of confidence are significantly below the critical bound of confidence of a homogeneous society.The phenomenon is shown by examples of agentbased simulation and by numerical computation of the time evolution of the agents density. The result holds for the bounded confidence model of Deffuant, Weisbuch and others (Weisbuch, G. et al ; Meet, discuss, and segregate!, Complexity, 2002, 7, 55-63), as well as for the model of Hegselmann and Krause (Hegselmann, R., Krause, U.; Opinion Dynamics and Bounded Confidence, Models, Analysis and Simulation, Journal of Artificial Societies and Social Simulation, 2002, 5, 2). Thus, given an average level of confidence, diversity of bounds of confidence enhances the chances for consensus. The drawback of this enhancement is that opinion dynamics becomes suspect to severe drifts of clusters, where open-minded agents can pull closedminded agents towards another cluster of closedminded agents. A final consensus might thus not lie in the center of the opinion interval as it happens

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“…This is probably due to the fact that the emergence of a collective state is a feature reminiscent of the behavior of many-particle systems in the fields of physics, chemistry and biology. Therefore, the formation of public opinion has been the subject of a number of recent works that, to some extent, capture the fundamental processes that determine the emergence or not of consensus within a population [1,2,3,4,5]. In Refs.…”

Section: Introductionmentioning

confidence: 99%

“…Additional results of similar models have been shown in Refs. [4,5], such as the relevance of the dynamical time scale on the formation of minorities and the role of a complex topology in the contact network. A more general class of models has been studied in Refs.…”

Section: Introductionmentioning

confidence: 99%

The dynamics of opinion in hierarchical organizations

Laguna

Gusman

Abramson

et al. 2005

Physica A: Statistical Mechanics and its Applications

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We study the mutual influence of authority and persuasion in the flow of opinion. Many social organizations are characterized by a hierarchical structure where the propagation of opinion is asymmetric. In the normal flow of opinion formation a high-rank agent uses its authority (or its persuasion when necessary) to impose its opinion on others. However, agents with no authority may only use the force of its persuasion to propagate their opinions. In this contribution we describe a simple model with no social mobility, where each agent belongs to a class in the hierarchy and has also a persuasion capability. The model is studied numerically for a three levels case, and analytically within a mean field approximation, with a very good agreement between the two approaches. The stratum where the dominant opinion arises from is strongly dependent on the percentage of agents in each hierarchy level, and we obtain a phase diagram identifying the relative frequency of prevailing opinions. We also find that the time evolution of the conflicting opinions polarizes after a short transient.

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Minorities in a model for opinion formation

Cited by 46 publications

References 8 publications

Continuous Opinion Dynamics Under Bounded Confidence: A Survey

Continuous Opinion Dynamics Under Bounded Confidence: A Survey

Heterogeneous bounds of confidence: Meet, discuss and find consensus!

The dynamics of opinion in hierarchical organizations

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