This paper studies information diffusion in social media and the role of bots in shaping public opinions. Using Twitter data on the 2016 E.U. Referendum ("Brexit") and the 2016 U.S. Presidential Election, we find that diffusion of information on Twitter is largely complete within 1-2 hours....

This paper presents market-based evidence that President Trump influences expectations about monetary policy. We use tick-by-tick fed funds futures data and a collection of Trump tweets criticizing the conduct of monetary policy and consistently advocating that the Fed lower interest rates....

During the course of the COVID-19 pandemic, a common strategy for public health organizations around the world has been to launch interventions via advertising campaigns on social media. Despite this ubiquity, little has been known about their average effectiveness. We conduct a large-scale...

We examine whether social networks facilitate online markets using data from a leading peer-to-peer lending website. We find that borrowers with social ties are consistently more likely to have their loans funded and receive lower interest rates; however, most borrowers with social ties are more...

It is not surprising that the financing of early-stage creative projects and ventures is typically geographically localized since these types of funding decisions are usually predicated on personal relationships and due diligence requiring face-to-face interactions in response to high levels of...

We model social media as collections of users producing and consuming content. Users value consuming content, but doing so uses up their scarce attention, and hence they prefer content produced by more able users. Users also value receiving attention, creating the incentive to attract an...

We use anonymized and aggregated data from Facebook to explore the spatial structure of social networks in the New York metro area. We highlight the importance of transportation infrastructure in shaping urban social networks by showingthat travel time and travel costs are substantially stronger...

We use aggregated data from Facebook to show that COVID-19 was more likely to spread between regions with stronger social network connections. Areas with more social ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally had more...

We document that the recent house price experiences within an individual's social network affect her perceptions of the attractiveness of property investments, and through this channel have large effects on her housing market activity. Our data combine anonymized social network information from...