Dynamics of Information Exchange in Endogenous Social Networks
We develop a model of information exchange through communication and investigate its implications for information aggregation in large societies. We define asymptotic learning as the fraction of agents taking the correct action converging to one as a society grows large. Under truthful communication, we show that asymptotic learning occurs if (and under some additional conditions, also only if) in the induced communication network most agents are a short distance away from “information hubs,” which receive and distribute a large amount of information.