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Opinion Dynamics and the Evolution of Social Power in Influence Networks (2015, background): “In boundedconfidence models, each individual interacts with only those individuals whose opinions are close enough to its own: synchronous [11] [40] [52] [58] as well as pairwise asynchronous [22] [74] updates have been studied.”
An Individual‐Based Model of Innovation Diffusion Mixing Social Value and Individual Benefit1 (2005, methodology): “The dynamics on the social values are based on the “relative agreement” model that we studied earlier (Deffuant et al. 2001; Weisbuch et al. 2002; Deffuant et al. 2002a).”
A tutorial on modeling and analysis of dynamic social networks. Part I (2017, background): “sophisticated are extensions of the DW models, involving nonlinear couplings among interacting agents (e.g. the “relative agreement” models [210, 214, 215, 219]), dynamic or random conﬁ- dence bounds [211, 220, 221], noises [222, 223] and “long-range” interactions (agents can assimilate opinions bey”
Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization (2017, background): “This has also been discussed in terms of committed minorities [63], individual inﬂexibility [64], close-minded agents [65], narrow-minded agents [61, 62], extremists [14, 16, 18, 66, 67], and stubborn agents or actors [68–70].”