Stability in Binary Opinion Diffusion

Abstract The paper studies the stabilization of the process of diffusion of binary opinions on networks. It first shows how such dynamics can be modeled and studied via techniques from binary aggregation, which directly relate to neighborhood frames. It then characterizes stabilization in terms of such neighborhood structures, and shows how the monotone \(\mu \) -calculus can express relevant properties of them. Finally, it illustrates the scope of these results by applying them to specific diffusion models.

Authors

• Zoé Christoff
• Davide Grossi

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