Drew Johnston

Unveiling the social fabric through a temporal, nation-scale social network and its characteristics - Scientific Reports Scientific Reports - Unveiling the social fabric through a temporal, nation-scale social network and its characteristics

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What does the social fabric of an entire country look like?
We built a nation-scale social network of Denmark — 7.2 million people, 1.4 billion ties, 14 years of data.
Here’s what we found 👇
📄 doi.org/10.1038/s415...
#NetworkScience #Sociology

I'm excited to present at @ic2s2.bsky.social in Norrköping! Wednesday at 10, I'll give a lightning talk about how to measure cross-class social connections (almost) everywhere on Earth. I'll also have two posters up in the Weds session. If you're here, I'd love to chat social networks, etc!

If you want to learn more, our paper describing the research is available here: drew-johnston.com/files/cross_...
(with bonus maps here: drew-johnston.com/files/cross_...)
and all the data is available to download at HDX: data.humdata.org/dataset/cros...

Can men and women be just friends? The answer matters more than you think

You can read the full article here: economist.com/internationa...
Many thanks to the team behind the research (
Mike Bailey, @ayushkumar.bsky.social, Theresa Kuchler, and Johannes Stroebel) and the team at the Economist (@ainsliejstone.bsky.social ) for making this all possible!

On the flip side, they find that labor force participation gaps are a better predictor of the rate of more marginal (top 200) friendships in a place.

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 🧵)

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:

We'd love to see you use the data in your own research.
You can download it at a variety of granularities here: data.humdata.org/dataset/cros...
and find the paper here: doi.org/10.1257/pand...
or on my website: drew-johnston.com/files/cross_...

Our paper describes the construction of the data, but we think there are still a ton of stories to tell from people who have more local context than we do. For instance, I'd like to know more about the differences we see here!

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:

Opinion | To Understand Global Migration, You Have to See It First These estimates, drawn from the location data of three billion Facebook users, provide a view of human migration in extraordinary detail.

An amazing visualization from the NYT of some research from my team:
www.nytimes.com/interactive/...

Stay tuned!

New data show that the class divide in Britain may not be so wide They make the country look better than America

I had a sneak peek at some data which is being published by Meta today, showing that Britain is less divided by class than you might expect: www.economist.com/britain/2025...

We use self-reported gender from individuals' profiles.

Would love to see something like this, but it would take a bunch of data work to pull off. Perhaps it's possible in the future if there's enough interest!

In the data release, we provide information about how common cross-gender ties are among the closest friendships relative to among less-close friendships; it might be possible to use this to say something about cross-country patterns in within-family friendships relative to more distant ones.

Great questions! I think the first few "closest" friendships are likely to be partners or family, though this is just an educated guess based on the fact that the closest few friendships display weaker gender homophily in most countries (see Figure 1 in the paper).

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!

My post is for the top 200 friends. And yes, it's very likely due to the different number over which the statistics are calculated! Check out the appendix to the paper, which has many maps plotted separately by N top friends: drew-johnston.com/files/cross_...

Thank you so much for your interest! Glad to hear that people find this interesting--one small note though, 1 here actually indicates no bias, not 0.5! I've copied the formula for the values here. You can see more details in the paper: drew-johnston.com/files/cross_...

This project sprung out of a collaboration with Mike Bailey, Theresa Kuchler, @ayushkumar.bsky.social, and Johannes Stroebel and would not have been possible without them!

We think our data is an appealing way to measure attitudes on gender, particularly in countries not often surveyed.
If you're interested in working with this data, download it here: data.humdata.org/dataset/cros...
The paper (out soon in AEA P+P) is available here: drew-johnston.com/files/cross_...

Across countries, the Cross-Gender Friending Ratio is strongly predictive of gender differences in labor force participation.
Within countries, we also find a strong correlations with gender attitudes in the World Values Survey, such as opinions about women's suitability for political office.

We measure gender differences using the Cross-Gender Friending Ratio, the ratio of female friends in men's networks to the share of female friends in women's networks in a given place.
Men almost always have a lower share of female friends than women do, but the degree varies across countries:

Have you ever wondered how social networks differ by gender?
Check out my team's new dataset, which uses Facebook data to measure regional differences in social networks by gender all across the world!
A 🧵 with examples, a description of our methodology, and a link to download the data:

We measure gender differences using the Cross-Gender Friending Ratio, the ratio of female friends in men's networks to the share of female friends in women's networks in a given place.
Men almost always have a lower share of female friends than women do, but the degree varies across countries:

Across countries, the Cross-Gender Friending Ratio is strongly predictive of gender differences in labor force participation.
Within countries, we also find a strong correlations with gender attitudes in the World Values Survey, such as opinions about women's suitability for political office.

We measure gender differences using the Cross-Gender Friending Ratio, the ratio of female friends in men's networks to the share of female friends in women's networks in a given place.
Men almost always have a lower share of female friends than women do, but the degree varies across countries:

Social capital I: measurement and associations with economic mobility - Nature Analyses of data on 21 billion friendships from Facebook in the United States reveal associations between social capital and economic mobility.

If you're considering an econ predoc, Theresa Kuchler + Johannes Stroebel are hiring a predoc to work on social networks projects, starting fall 2025. They are wonderful to work with and do very cool research (see www.nature.com/articles/s41...) . Apply at: apply.interfolio.com/161883

I'm presenting "Social Capital Around the World" Saturday @ 8am at AEAs. We use data from 2.5 billion Facebook accounts to measure cross-class and cross-gender friendships globally, and explore how they connect to downstream outcomes like intergenerational mobility. www.aeaweb.org/conference/2...