DP16932 A Model of Online Misinformation
We present a model of online content sharing where agents sequentially observe an article and
must decide whether to share it with others. This content may or may not contain misinformation.
Agents gain utility from positive social media interactions but do not want to be called out for
propagating misinformation. We characterize the (Bayesian-Nash) equilibria of this social media
game and show sharing exhibits strategic complementarity. Our first main result establishes that
the impact of homophily on content virality is non-monotone: homophily reduces the broader
circulation of an article, but it creates echo chambers that impose less discipline on the sharing of
low-reliability content. This insight underpins our second main result, which demonstrates that
social media platforms interested in maximizing engagement tend to design their algorithms to
create more homophilic communication patterns (“filter bubbles”). We show that platform incentives
to amplify misinformation are particularly pronounced for low-reliability content likely to
contain misinformation and when there is greater polarization and more divisive content. Finally,
we discuss various regulatory solutions to such platform-manufactured misinformation.