Information Aggregation on Networks: an Experimental Study

About this event

We study the impact of network architecture on the efficiency of information transmission and dynamics of learning in large networks using laboratory experiments. While the theoretical literature has recently made progress in identifying the geometric features of networks that enable the flow of information and those that impede it, the empirical literature lags behind. Our project will fill this gap by designing a novel interface that allows for studying the interplay between network architecture and information diffusion in large networks in a controlled laboratory environment. In particular, we address the following questions: How do network structures affect the likelihood of reaching a consensus? Conditional on reaching the consensus, how likely agents are to choose the correct action? How fast convergence occurs? Is it possible at all to observe consensus in large networks? Is it possible to observe connected networks in which agents agree to disagree?