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...

Purpose: This paper addresses the nature, formalization, and neural bases of (affective) social ties anddiscusses the relevance of ties for health economics. A social tie is defined as an affectiveweight attached by an individual to the well-being of another individual...

Can online social contacts replace the importance of real-life social connections in our pursuit of happiness? With the growing use of social network sites (SNSs), attention has been increasingly drawn to this topic. Our study empirically examines the effect of SNS use on happiness for different...

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...

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...

A fundamental question in social sciences is how trust emerges. We provide an answer which relies on the formation of social and economic relationships. We argue that behind trust lies the fact that individuals invest in connections taking into account the potential externalities networks...