Continuous Opinion Dynamics under Bounded Confidence: A Survey

By Jan Lorenz. 2007

702 citations recorded by the source corpus.

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 such 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 o...

Subfields: Economics and Econometrics, Modeling and Simulation, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/11cc155e624a630b2e715ceac4516a7ce6586eef

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Citations in the corpus

Statistical physics of social dynamics (2007, methodology): “BC models have been recently reviewed in (Lorenz, 2007).”
Novel Multidimensional Models of Opinion Dynamics in Social Networks (2015, background): “…aforementioned models of opinion dynamics deal with scalar opinions, we deal with inﬂuence that may modify opinions on several topics, which makes it natural to consider vector-valued opinions [6], [33]–[35]; each opinion vector in such a model is constituted by d > 1 topic-speciﬁc scalar opinions.”
Networks beyond pairwise interactions: structure and dynamics (2020, background): “In these cases, the opinion of an individual might be better represented by a continuous variable xi ∈ [0,1] spanning between two extremes [512, 513].”
Models of Social Influence: Towards the Next Frontiers (2017, background): “Comprehensive reviews can be found in Lorenz (2007) or Castellano et al. (2009).”
Clustering and asymptotic behavior in opinion formation (2014, background): “1 Introduction Thanks to the development of social media, the dynamics of opinion formation has recently generated much interest [1,4,10,11,17,20,21].”
Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization (2017, methodology): “This representation has been used extensively in the opinion dynamics literature (see [12] for a review of the history of these assumptions).”
On the control through leadership of the Hegselmann–Krause opinion formation model (2015, neutral): “[2, 7, 17, 24, 25].”
On Krause's Multi-Agent Consensus Model With State-Dependent Connectivity (2008, methodology): “The model (1) can of course be extended to higher dimensional spaces, as is often done in the opinion dynamics literature (see [24] for a survey).”
Manufacturing Consent (2015, background): “, social impact [11], bounded confidence [8], Bayesian learning [12].”
Social Influence and the Collective Dynamics of Opinion Formation (2013, background): “Likewise, the fact that individuals holding completely different beliefs exert very little influence on each other is consistent with the idea of “bounded confidence”—a modeling concept suggesting that social influence is negligible when opinions are initially too distant [20,26].”
Continuous and discontinuous opinion dynamics with bounded confidence (2012, background): “Many models developed by physicists [15, 16] involve difference equations, because they were intended to be simulated by computers.”