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Opinion Formation On Adaptive Networks With Intensive Average Degree, Beate Schmittmann, Abhishek Mukhopadhyay

Beate Schmittmann

We study the evolution of binary opinions on a simple adaptive network of N nodes. At each time step, a randomly selected node updates its state (“opinion”) according to the majority opinion of the nodes that it is linked to; subsequently, all links are reassigned with probability p̃ (q̃ ) if they connect nodes with equal (opposite) opinions. In contrast to earlier work, we ensure that the average connectivity (“degree”) of each node is independent of the system size (“intensive”), by choosing p̃ and q̃ to be of O(1/N). Using simulations and analytic arguments, we determine the final steady states …