Ayush Kumar
@aylovedata
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Econ Predoc at NYU, UGA Alumnus, interested in questions that make you say “how is this economics?” Incoming PhD Student Northwestern Economics
New York, USA
Joined January 2022
RT @drew_m_johnston: I'm excited to present at @IC2S2 in Norrköping! Wednesday at 10, I'll give a lightning talk about how to measure cross….
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RT @drew_m_johnston: The Economist published an article today about my team's research on measuring social ties between men and women. The….
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RT @drew_m_johnston: My team's paper on cross-gender friendships is out today in the AEA Papers & Proceedings. We use data from Facebook to….
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RT @guyabelguyabel: 📢New paper out on measuring global #migration flows using online data in @PNASNews . We use privacy-protected records f….
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RT @arpitrage: 📢Heavily revised working paper on AI + Zoning — . with @AlexBartik and @DMilo75, we have a new draft of our paper which expa….
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RT @sheemawn: Super ciekawa analiza NYT - w latach 2019-22 do 🇵🇱 przyjechało o 1 mln osób więcej niż z niej wyjechało:.- największe saldo o….
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RT @_alice_evans: Analysis of 1.38 trillion Facebook connections reveals the areas (in deep red) where male-female ties are rare. Fantasti….
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This project was super fun. It’s also my first paper! There’s plenty more in the pipeline where that came from. We hope people will use our data to learn more about the determinants and effects of cross-gender friendships. Data:
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To close out, here are some additional maps of Asia. We have plenty more maps in our online appendix:
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Our data precisely measures one dimension of gender relations: friendship. CGFR does correlate with more progressive attitudes on gender. But this is not a causal claim — there is likely significant reverse causality & culture is an important omitted variable.
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@arpitrage pointed to Maharashtra as unusual because it’s seen as relatively progressive but has a very low CGFR. In India, CGFR is much higher in predominantly Christian states. If I had to guess, culture is the most important determinant of CGFR.
Maharashtra is a bit puzzling here. Punjab and Haryana being bad on gender is well known and tracks other data. But Maharashtra typically ranks well on socioeconomic measures of progress. Maybe it has to do with migrants?.
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The natural question is why? We explored a rich set of covariates from the ACS and found that the racial/demographic composition of the county was by far the strongest correlate of CGFR (over top-200 friends).
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More findings on cross-gender friending: In addition to the maps @drew_m_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. 🧵
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 download link:
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RT @powerfultakes: More comprehensive map of M/F friendship frequency on Facebook. Now including Ukraine and some Russian cities. https://….
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RT @_alice_evans: SHOUT OUT TO ALL MY AMAZING MALE FRIENDS!. I absolutely love this paper by @drew_m_johnston, Kuchler, @michaelcbailey, Ku….
ggd.world
A phenomenal new paper by Bailey, Johnston, Kuchler, Kumar and Stroebel offers unprecedented insights into gender relations through an extraordinary dataset of 1.38 trillion Facebook connections.
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RT @sheemawn: Super ciekawe dane. Pokusiłem się o dodatkowe mapki dla Europy. Top 5 znajomych: przeciętnie mężczyźni mają o około połowę….
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RT @josh_coven: 1/ Excited to share a thread about my JMP: The Impact of Institutional Investors on Homeownership and Neighborhood Access.h….
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RT @paulnovosad: 🤷🤷♀️New data: SHRUG 2 is out!! @devdatalab has been working on this for two years, a HUGE update to India’s coolest data….
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RT @OppInsights: Curious about #bigdata social science research? Want to hone your #research skills and join a team dedicated to improving….
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