We explore how social network exposure to COVID-19 cases shapes individuals’ social distancing behavior during the early months of the ongoing pandemic. We work with de-identified data from Facebook to show that U.S. users whose friends live in areas with worse coronavirus outbreaks reduce...

This paper contributes to the literature on public health communication by studying how the framing of a message relaying the forecast impact of COVID-19 prevention measures affects compliance behaviour amongst both the young and old. A representative sample of survey respondents in the UK and...

Homophily is typically measured using a single dimension to define groups. However, people generally display preferences over multiple dimensions. I develop a simple model that characterizes agents both by a (discrete) "type" and a (continuous) "personality" value. Agents have...

This paper introduces a new mechanism through which positive externality spills over in a network. We find that the introduction of the new spillover mechanism plays a major role in reducing the set of Nash equilibrium though at the same time it increases the set of stable equilibria in a...

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 explore how social network exposure to COVID-19 cases shapes individuals' social distancing behavior during the early months of the ongoing pandemic. We work with de-identified data from Facebook to show that U.S. users whose friends live in areas with worse coronavirus outbreaks reduce their...

We examine how three different communication processes operating through social networks are affected by homophily - the tendency of individuals to associate with others similar to themselves. Homophily has no effect if messages are broadcast or sent via shortest paths; only connection density...

We study a sequential-learning model featuring a network of naive agents with Gaussian information structures. Agents apply a heuristic rule to aggregate predecessors' actions. They weigh these actions according the strengths of their social connections to different predecessors. We show this...

This paper contributes to the literature on public health communication by studying how the framing of a message relaying the forecast impact of COVID-19 prevention measures affects compliance behaviour amongst both the young and old. A representative sample of survey respondents in the UK and...

Why do people appear to forgo information by sorting into “echo chambers”? We construct a highly tractable multi-sender, multi-receiver cheap talk game in which players choose with whom to communicate. We show that segregation into small, homogeneous groups can improve everybody’s...