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Showing 1–5 of 5 articles

  • Viral Polls Are Not Representative Polls

    Political scientist Kevin Reuning scrapes 90 days of poll posts from a prolific Bluesky polling account, extracts each result with an LLM, and shows that the polls that get reposted most are the ones that look better for Democrats than the race average, so people who follow polls through their feeds see a skewed picture.

    Research · Data Science · Politics · Social Media

    5 min · 1,131 words

  • How many stars does it take to find a cluster?A pre-registered search for co-moving stars in Gaia DR3, and an honest measure of what it can and cannot see.

    Shaurya describes a pre-registered search for groups of co-moving stars within about 500 parsecs of the Sun using Gaia DR3. The pipeline recovers known clusters and its sensitivity is measured by injection tests (roughly 10 surviving members beyond 140 pc), but it produces too many false positives to trust a new detection, and a classifier did not fully fix that.

    Research · Astronomy · Science · Data Science · Open Science

    6 min · 1,475 words

  • The Economic Complexity of the Western Roman Empire

    Michele Coscia explains how he and co-authors inferred the economic complexity of the Western Roman Empire from occupations recorded in Latin inscriptions (the LIST dataset), correcting for status and gender biases. Latium scored highest, and Roman-era complexity for modern-country territories correlates significantly with present-day Economic Complexity Index values.

    Research · Economics · History · Data Science · Network Science

    4 min · 935 words

  • Positron October Release Highlights

    Positron is Posit’s new, next-generation IDE for data science. Positron is designed to be an extensible, polyglot tool for exploring data and reproducible authoring in Python, R, and more.

    Changelog · Developer Tools · Open Source · Data Science · Announcements

    6 min · 1,320 words

  • A Model for Winning Survivor

    The new season of Survivor airs next week. My favorite thing about watching Survivor is arguing about the strategy of the show: who should have won the season? Is it better to play under the radar? Or does making big moves set you up to win? Who is the greatest player of all time: Cirie? Tony? Boston Rob? I thought it’d be fun to build a machine learning model to help answer these questions.

    Case study · Data Science · Machine Learning · Modeling

    13 min · 3,012 words