Characterizes the distributional mean-field limit of co-evolving latent space networks with feedback, including empirical measures and graphon convergence, via a conditional propagation of chaos result.
Sznajd-Weron and J
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
Simulations of a modified Axelrod model on scale-free networks with continuous opinions reveal polarization trends, with empathetic agents showing limited success unless highly connected agents alter their behavior.
citing papers explorer
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Mean-Field Analysis of Latent Variable Process Models on Dynamically Evolving Graphs with Feedback Effects
Characterizes the distributional mean-field limit of co-evolving latent space networks with feedback, including empirical measures and graphon convergence, via a conditional propagation of chaos result.
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Modified Axelrod Model Showing Opinion Convergence And Polarization In Realistic Scale-Free Networks
Simulations of a modified Axelrod model on scale-free networks with continuous opinions reveal polarization trends, with empathetic agents showing limited success unless highly connected agents alter their behavior.