Strategic Learning and the Topology of Social Networks
Elchanan Mossel, Allan Sly, Omer Tamuz
Econometrica · 2015 · Volume 83 · Issue 5
Abstract
We consider a group of strategic agents who must each repeatedly take one of two possible actions. They learn which of the two actions is preferable from initial private signals and by observing the actions of their neighbors in a social network. We show that the question of whether or not the agents learn efficiently depends on the topology of the social network. In particular, we identify a geometric “egalitarianism” condition on the social network that guarantees learning in infinite networks, or learning with high probability in large finite networks, in any equilibrium. We also give examples of nonegalitarian networks with equilibria in which learning fails.
Keywords
Social learning, informational externalities, social networks, aggregation of information
Enable JavaScript for citation tools and additional paper interactions.