Learning from like-minded people

We propose a social learning model where agents choose who to communicate with based on the trade-off between collecting information and influencing others' actions. Like-minded people reveal more truthful information, but talking to someone different makes an agent more likely to influence another person's action, because like-minded people will take similar actions anyway. In our model agents start with heterogeneous priors about an unknown state of the world. First agents form coalitions of communication partners. Then everyone observes a private i.i.d. signal and sends a message to her partner. Finally everyone takes an action based on her prior, her private signal, and her partner's message. Our main finding is that when signals and actions are binary, agents form assortative coalitions, even though assortative coalitions are inefficient for social welfare.