, and showed that it gives a lower bound on the time it takes for a certain natural best-reply or learning process operating …

We study learning and influence in a setting where agents communicate according to an arbitrary social network and …

determine the speed of social learning. To this end, we study a variant of the seminal model of DeGroot (1974), according to … learning has a simple analytical characterization in terms of the relative entropy of agents’ signal structures and their … non-trivial implications for the rate of learning. In particular, we show that when the informativeness of different …

concerning the role of those characteristics in determining learning, diffusion, decisions, and resulting behaviors. We also …

We study social learning in a social network setting where agents receive independent noisy signals about the truth …

We analyze boundedly rational learning in social networks within binary action environments. We establish how learning … induces learning (i.e., convergence to the optimal action for every agent in every connected network) only in highly … asymmetric environments. In all other environments learning fails in networks with a diameter larger than four. Finally, we …

We study perfect Bayesian equilibria of a sequential social learning model in which agents in a network learn about an … neighbors are mutually independent. We introduce a new metric of information diffusion in social learning, which is weaker than …

We study social learning in a social network setting where agents receive independent noisy signals about the truth …

for behavioral observational learning in social networks. We show that a seller could potentially control the information … available to future customers and induce behavioral observational learning by using an information-revealing pricing strategy … networks. It could prevent the behavioral observational learning that would increase future customers' willingness to pay …

This paper examines social learning when only one of the two types of decisions is observable. Because agents arrive …, as in the standard model, learning is complete if and only if signals are unbounded. If signals are bounded, cascades may …