In online social networks, social information, i.e., content generated and shared by users (e.g., past purchases), can be a substitute for sponsored advertising, which constitutes the network's main source of revenue. When will social information be let to spread freely over the platform? We...

In online social networks, social information, i.e., content generated and shared by users (e.g., past purchases), can be a substitute for sponsored advertising, which constitutes the network’s main source of revenue. When will social information be let to spread freely over the platform? We...

We consider a general model of boundedly rational opinion formation in social networks. Some agents are initially exposed to misinformation resulting in misspecified prior beliefs. All agents receive a normal, unbiased signal of the true state and subsequently interact repeatedly by announcing...

We analyze boundedly rational learning in social networks within binary action environments. We establish how learning outcomes depend on the environment (i.e., informational structure, utility function), the axioms imposed on the updating behavior, and the network structure. In particular, we...

We consider a dynamic market with two firms that sell competing common-value products. The firms offer both products to an infinite set of rational consumers. Each consumer observes a conditionally independent and identically distributed private signal about the product qualities. Consumers...

We analyze boundedly rational updating from aggregate statistics in a modelwith binary actions and binary states. Agents each take an irreversible action in sequence after observing the unordered set of previous actions. Each agent first forms her prior based on the aggregate statistic, then...

We analyze boundedly rational learning in social networks within binary action environments. We establish how learning outcomes depend on the environment (i.e., informational structure, utility function), the axioms imposed on the updating behavior, and the network structure. In particular, we...

We analyze boundedly rational updating in a repeated interaction network model with binary actions and binary states. Agents form beliefs according to discretized DeGroot updating and apply a decision rule that assigns a (mixed) action to each belief. We first show that under weak assumptions...

We analyze boundedly rational learning in social networks within binary action environments. We establish how learning outcomes depend on the environment (i.e., informational structure, utility function), the axioms imposed on the updating behavior, and the network structure. In particular, we...