This paper investigates opinion dynamics and social influence in directed communication networks. We study the properties of a generalized boundedly rational model of opinion formation in which individuals aggregate the information they receive by using weights that are a function of their neighbors’ indegree. We then present an experiment designed to test the predictions of the model. We find that both Bayesian updating and boundedly rational updating à la DeMarzo et al. (2003) are rejected by the data. Consistent with our theoretical predictions, the social influence of an agent is positively and significantly affected by the number of individuals she listens to. When forming their opinions, agents do take into account the structure of the communication network, although in a sub-optimal way.
|Keywords:||Social Networks, Learning, Social In uence, Bounded Rationality|
|JEL:||D85 D83 A14 L14 Z13|