Opinion dynamics and bounded confidence: models, analysis and simulation

By R. Hegselmann, Ulrich Krause. Journal of Artificial Societies and Social Simulation, 2002

3,246 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/146082c908eae45f8e6e8db0c94916223304a4c1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

The structure and dynamics of multilayer networks (2014, background): “Up to now, various spin-like setups have been put forward to study the evolution of opinion dynamics, which include the Sznajd model [290], majority rule model [291,292], bounded confidence model [288,293], and voter model [294,295], to name but a few.”
Debiasing social wisdom (2013, background): “There is a line of impressive work that studied the consensus and fragmentation of the expressed opinions at steady state using different models of opinion formation [9, 13, 3, 2].”
On the control through leadership of the Hegselmann–Krause opinion formation model (2015, background): “Indeed it is known[22, 7] that the system in free evolution tends to clusters.”
Opinion dynamics in social networks with stubborn agents: Equilibrium and convergence rate (2014, unknown): “Key words: Multi-agent systems, Markov models, Equilibrium, Eigenvalues”
Understanding Polarization: Meanings, Measures, and Model Evaluation (2017, methodology): “In an influential series of articles, Hegselmann and Krause develop a ‘bounded confidence’ model of opinion polarization that functions in terms of mutual influence among those within a specific threshold of similarity (Hegselmann and Krause 2002, 2005, 2006).”
Mean-field and graph limits for collective dynamics models with time-varying weights (2020, unknown): “(4) We point out that the choice m i = 1 and ψ (N) i ≡ 0 for all i ∈ {1, · · · , N} brings us back to the classical Hegselmann-Krause model for opinion dynamics [15]: d dt xi (t) = 1 N N ∑”
Novel Multidimensional Models of Opinion Dynamics in Social Networks (2015, background): “This principle is prominently manifested by various bounded conﬁdence models, where the agents completely ignore the opinions outside their conﬁdence intervals [4]–[7].”
Modelling dynamical processes in complex socio-technical systems (2011, background): “In other instances, further realism has been introduced by the use of continuous opinion variable”
Agent-Based Modeling: A New Approach for Theory Building in Social Psychology (2007, unknown): “Social influence is a core social psychological topic that has received a substantial amount of attention from ABM theorists in several disciplines including sociology, economics, and even physics (Friedkin, 1999; Hegselmann & Krause, 2002; Janssen & Jager, 2001).”
Convergence Speed in Distributed Consensus and Averaging (2009, unknown): “In particular, the seminal paper [31] introduced a popular and mathematically appealing model of opinion fragmentation.”
Continuous Opinion Dynamics under Bounded Confidence: A Survey (2007, methodology): “It was analyzed through computer simulations by Hegselmann and Krause (8) in the”
The Pontryagin Maximum Principle in the Wasserstein Space (2017, background): “More generally, the study of other kind of interacting agents, such as opinion dynamics on networks [9, 28], or animal flocks [7, 18], has been conveyed with similar techniques.”
Agent-based simulation of innovation diffusion: a review (2011, background): “The author incorporates the idea of “bounded conﬁdence” (cf. Hegselmann and Krause 2002) by assuming that consumers with similar opinions tend to form stronger bonds while those with very different opinions tend to diminish the level of received inﬂu-ence.”
Clustering and asymptotic behavior in opinion formation (2014, methodology): “Different models have been introduced to study opinion dynamics [2, 3, 10, 12, 13, 15–17, 21].”