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 use de-identified data from Facebook to study the social integration of Syrian migrants in Germany, a country that received a large influx of refugees during the Syrian Civil War. We construct measures of migrants’ social integration based on Syrians’ friendship links to Germans, their...

We use de-identified data from Facebook to study the social integration of Syrian migrants in Germany, a country that received a large influx of refugees during the Syrian Civil War. We construct measures of migrants’ social integration based on Syrians’ friendship links to Germans, their...

We use de-identified data from Facebook to study the social integration of Syrian migrants in Germany, a country that received a large influx of refugees during the Syrian Civil War. We construct measures of migrants' social integration based on Syrians' friendship links to Germans, their use of...

We introduce, analyze, and describe subnational data on cross-gender friendships for nearly 200 countries and territories, using data from 1.38 trillion ties between 1.8 billion Facebook users. Homophily by gender exists nearly everywhere, with individuals' strongest ties exhibiting less...

We use anonymized and aggregated data from Facebook to show that areas with stronger social ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March 30, 2020. These relationships hold after...

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...