Social Learning and Social Context

People gather information from their peers to improve their decisions in many situations. I investigate the impact of a communication friction on which social learning networks form and on the quality of information transferred over these networks. In my model, agents cannot perfectly communicate their beliefs because of agent-level idiosyncrasies in expression. Social context (knowing what information a peer receives from her peers) allows one to better understand these idiosyncrasies and so better understand their information. If agents have sufficient time to communicate, a directed cycle network allows all agents to learn all information in society despite the idiosyncrasies in expression. With more limited time to exchange information, agents must trade off the reach of their network (i.e., from how many agents they will receive some information) with the clarity of the announcements (i.e., how well they learn the signal of any one agent they observe). Social context acts as a substitute for familiarity and can result in novel non-monotonicities in overall welfare with varying underlying parameters.