Social Inequality and the Spread of Misinformation

We study the spread of misinformation in a social network characterized by unequal access to learning resources. Agents use social learning to uncover an unknown state of the world, and a principal strategically injects misinformation into the network to distort this learning process. A subset of agents throughout the network is endowed with knowledge of the true state. This gives rise to a natural definition of inequality: privileged communities have unrestricted access to these agents, whereas marginalized communities do not. We show that the role that this inequality plays in the spread of misinformation is highly complex. For instance, communities who hoard resources and deny them to the larger population can end up exposing themselves to more misinformation. Conversely, although more inequality generally leads to worse outcomes, the prevalence of misinformation in society is nonmonotone in the level of inequality. This implies that policies that decrease inequality without substantially reducing it can leave society more vulnerable to misinformation. This paper was accepted by Baris Ata, stochastic models and simulation.