This paper investigates opinion dynamics and social influence in directed communication networks. We study the theoretical properties of a boundedly rational model of opinion formation in which individuals aggregate the information they receive from their neighbors by using weights that are a...

We introduce two pieces of information, denoted memes, into a diffusion process in which memes are transmitted when individuals meet and forgotten at an exogenous rate. At most one meme can be transmitted at a meeting, which introduces opportunity costs in the process. Individuals differ...

We study a dynamic model of opinion formation in social networks. In our model, boundedly rational agents update opinions by averaging over their neighbors' expressed opinions, but may misrepresent their own opinion by conforming or counter-conforming with their neighbors. We show that an...

We investigate the role of manipulation in a model of opinion formation. Agents repeatedly communicate with their neighbors in the social network, can exert effort to manipulate the trust of others, and update their opinions about some common issue by taking weighted averages of neighbors'...

The novelty of our model is to combine models of collective action on networks with models of social learning. Agents are connected according to an undirected graph, the social network, and have the choice between two actions: either to adopt a new behavior or technology or stay with the default...

In the presence of dispersed information, agents may decide to take into account the actions of other agents because of the possible additional information conveyed by these actions. We call the act of using other agents' actions in the individual decision process social learning. This paper...

We study a model of social learning in networks where the dynamics of beliefs are driven by conversations of dissonance-minimizing agents. Given their current beliefs, agents make statements, tune them to the statements of their associates, and then revise their beliefs. We characterize the...

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 study private communication in social networks prior to a majority vote on two alternative policies. Some (or all) agents receive a private imperfect signal about which policy is correct. They can, but need not, recommend a policy to their neighbors in the social network prior to the vote. We...

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,...