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Opinion diffusion and campaigning on society graphs

Publication at Faculty of Mathematics and Physics |
2022

Abstract

We study the effects of campaigning, where the society is partitioned into voter clusters and a diffusion process propagates opinions in a network connecting the clusters. Our model can incorporate different campaigning actions, various partitions of the society into clusters and very general diffusion processes.

Perhaps surprisingly, we show that computing the cheapest campaign for rigging a given election can usually be done efficiently, even with arbitrarily-many voters. Moreover, we report on computational simulations we have performed to evaluate the quality and efficiency of finding such solutions.