In the last few years, breakthroughs in computational and experimental techniques have
produced several key discoveries in the science of networks and human collective …

This survey covers models of how agents update behaviors and beliefs using information
conveyed through social connections. We begin with sequential social learning models, in …

A longstanding problem in the social, biological, and computational sciences is to determine
how groups of distributed individuals can form intelligent collective judgments. Since …

This paper develops a model of Bayesian learning from online reviews and investigates the
conditions for learning the quality of a product and the speed of learning under different …

Social learning is the updating of beliefs based on observation of others. Such observation
can lead to efficient aggregation of information, but also to inaccurate decisions, fragility of …

How do social networks influence the decision to migrate? Prior work suggests two distinct
mechanisms that have historically been difficult to differentiate: as a conduit of information …

The pervasive diffusion of Social Networks (SN) produced an unprecedented amount of
heterogeneous data. Thus, traditional approaches quickly became unpractical for real life …

We exhibit a natural environment, social learning among heterogeneous agents, where
even slight misperceptions can have a large negative impact on long‐run learning …

We theoretically and empirically study an incomplete information model of social learning.
Agents initially guess the binary state of the world after observing a private signal. In …

We study belief formation in social networks using a laboratory experiment. Participants in
our experiment observe an imperfect private signal on the state of the world and then …