We investigate market selection and bet pricing in a simple Arrow security economy which we show is equivalent to the repeated prediction market models studied in the literature. We derive the condition for long run survival of more than one agent (the crowd) and quantify the information content...

We investigate market selection and bet pricing in a simple Arrow security economy which we show is equivalent to the repeated prediction market models studied in the literature. We derive the condition for long run survival of more than one agent (the crowd) and quantify the information content...

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'...

We present a model of opinion formation where individuals repeatedly engage in discussion and update their opinion in a social network similarly to the DeGroot model. Abstracting from the standard assumption that individuals always report their opinion truthfully, agents in our model may state...

We study social learning in a social network setting where agents receive independent noisy signals about the truth. Agents naïvely update beliefs by repeatedly taking weighted averages of neighbors' opinions. The weights are fixed in the sense of representing average frequency and intensity of...

We investigate how the selection process of a leader affects team performance with respect to social learning. We use a lab experiment in which an incentivized guessing task is repeated in a star network with the leader at the center. Leader selection is either based on competence, on...

We study the impact of bots on social learning in a social network setting. Regular agents receive independent noisy signals about the true value of a variable and then communicate in a network. They na¨ıvely update beliefs by repeatedly taking weighted averages of neighbors' opinions. Bots...