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Realized I forgot a to include a map of cross-gender social ties in North America--details on the methodology (and a link to the data) can be found in the original thread!

More findings on cross-gender friending: In addition to the maps Drew Johnston shared of CGFR over top-200 friends, we produce analogous measures over top-{10,25,50,100} friends. The spatial patterns between these maps can look quite different — for instance, in the US. 🧵

New data from Facebook reveals interesting patterns of cross-gender social ties around the world, from Michael Bailey, Drew Johnston, Theresa Kuchler, Ayush Kumar, and @stroebel_econ nber.org/papers/w33480

Analysis of 1.38 trillion Facebook connections reveals the areas (in deep red) where male-female ties are rare. Fantastic work by Drew Johnston, Kuchler, Michael Bailey, Kuchler, Ayush Kumar & Stroebel Featured in my TedTalk

📢New paper out on measuring global #migration flows using online data in PNASNews We use privacy-protected records from over 3 billion Facebook users to estimate migration flows between 181 countries, accounting for biases in social media usage. 🔗pnas.org/doi/10.1073/pn…

We are thrilled about last week’s launch of the Spanish Opportunity Lab in Madrid, founded by OI research associate @javiersoriaesp, who also developed the Spanish Opportunity Atlas. Explore their first working paper on mobility in Spain and more: 🔗 labdeoportunidades.com/en/

My team's paper on cross-gender friendships is out today in the AEA Papers & Proceedings. We use data from Facebook to show where connections between men and women are more (blue) and less (red) common, in almost every country, and release the data publicly! A 🧵 of maps:

The Economist published an article today about my team's research on measuring social ties between men and women. The article had cool original analyses, including showing that the rate of cross-gender ties among close (top 5) friends is predicted by an index of sexism (a 🧵)