This paper proposes a tractable model that allows us to analyze how agents' perception of relationships with others determines the structures of networks. In our model, agents are endowed with their own multidimensional characteristics and their payoffs depend on the social distance between...

This paper provides a formal characterization of the process of rational learning in social networks. Agents receive initial private information and select an action out of a choice set under uncertainty in each of infinitely many periods, observing the history of choices of their neighbors....

We develop a model of information exchange through communication and investigate its implications for information aggregation in large societies. An \textit{underlying state} determines payoffs from different actions. Agents decide which others to form a costly \textit{communication link} with,...

We study perfect Bayesian equilibria of a sequential social learning model in which agents in a network learn about an underlying state by observing neighbors' choices. In contrast with prior work, we do not assume that the agents' sets of neighbors are mutually independent. We introduce a new...

We study binary action network games with strategic complementarities. An agent acts if the aggregate social influence of her friends exceeds a transfer levied on the agent by a principal. The principal seeks to maximize her revenue while inducing everyone to act in a unique equilibrium. We...

We develop a dynamic framework of strategic information transmission through cheap talk in a social network. Privately informed agents have different preferences about the action to be implemented by each agent and repeatedly communicate with their neighbors in the network. We first characterize...

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...

This paper provides a formal characterization of the process of rational learning in social networks. Agents receive initial private information and select an action out of a choice set under uncertainty in each of infinitely many periods, observing the history of choices of their neighbors....

We develop a model of information exchange through communication and investigate its implications for information aggregation in large societies. An \textit{underlying state} determines payoffs from different actions. Agents decide which others to form a costly \textit{communication link} with,...

We study perfect Bayesian equilibria of a sequential social learning model in which agents in a network learn about an underlying state by observing neighbors' choices. In contrast with prior work, we do not assume that the agents' sets of neighbors are mutually independent. We introduce a new...