Opinion dynamics with emergent collective memory: A society shaped by its own past

Physica A: Statistical Mechanics and its Applications(2020)

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摘要
In order to understand the development of common orientation of opinions in the modern world we propose a model of a society described as a large collection of agents that exchange their expressed opinions under the influence of their mutual interactions and external events. In particular we introduce an interaction bias which results in the emergence of a collective memory such that the society is able to store and recall information coming from several external signals. Our model shows how the inner structure of the society and its future reactions are shaped by its own history. We provide an analytical explanation of such mechanism and we study the features of external influences with higher impact on the society. We show the emergent similarity between the reaction of a society modelled in this way and the Hopfield-like mechanism of information retrieval in Neural Networks.
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