work in progress

Higher Order Uncertainty in Social Learning
Last updated: March 08, 2018


This paper studies how uncertainty about the reliability of information sources affects the equilibrium outcome in a model of rational social learning. Agents are located on nodes of an exogenously given network and are endowed with noisy private signals about an underlying state of the world. They face uncertainty about the signal distribution and need to decide which of their neighbors to rely on when forming their opinions. The two core concepts of interest are learning and agreement. I show that agents exhibit a confirmation bias, relying predominantly on neighbors who observe similar signals, and that uncertainty can help explain disagreement on factual questions.

Information Manipulation and Propagation in Social Networks
Last updated: September 14, 2017


This paper presents a model of a manipulator trying to influence the collective decision of a population of agents. The novelty is to capture Bayesian persuasion followed by information diffusion in a network. Unbiased agents want the collective decision to match an unknown state of the world, while biased agents share the preferences of the manipulator. The manipulator controls the distribution of a signal. Agents communicate at a cheap talk stage. The manipulator faces a trade-off between a higher degree manipulation and higher information diffusion. The optimal degree of manipulation is inversely related to the density of biased agents.