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zeynep's profile
zeynep tufekci
zeynep tufekci
zeynep tufekci
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@zeynep

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zeynep tufekciVerified account

@zeynep

Complex systems, wicked problems. Society, technology, science and more. @UNC professor. @NYTimes columnist. My newsletter is @insight: http://www.theinsight.org 

floating in a most peculiar way
theinsight.org
Joined August 2009

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    1. G. Elliott Morris‏Verified account @gelliottmorris 3 Nov 2020

      G. Elliott Morris Retweeted zeynep tufekci

      I don’t know about this... Forecasts in general can definitely be wrong. Assigning a 99% chance to Clinton winning, for example, was a modeling error. If you don’t have the outcome in your prediction interval, from a modeling standpoint you very likely did something wrong.https://twitter.com/zeynep/status/1323649467015376896 …

      G. Elliott Morris added,

      zeynep tufekciVerified account @zeynep
      If you're looking for a distraction: Excellent academic article from @StatModeling @JessicaHullman @CBWlezien, @gelliottmorris & @JessicaHullman on communicating about forecasts—what they are, what they aren't. Again: the forecasts aren't wrong! Or right! https://twitter.com/JessicaHullman/status/1322981825040523271 …
      Show this thread
      8 replies 8 retweets 171 likes
      Show this thread
    2. zeynep tufekci‏Verified account @zeynep 3 Nov 2020
      Replying to @gelliottmorris

      How is it wrong? Trump had one percent chance, that model claimed, and that happened. I don't think it was a great model, but I don't see how it's wrong. One percent events happen, obviously, and we worry about them and change our whole lives over it: see COVID CFR.

      11 replies 1 retweet 17 likes
    3. G. Elliott Morris‏Verified account @gelliottmorris 3 Nov 2020
      Replying to @zeynep

      If you build a model that predicts 5 million deaths from COVID over the next month, but we only have 50k, is it wrong?

      5 replies 0 retweets 17 likes
    4. zeynep tufekci‏Verified account @zeynep 3 Nov 2020
      Replying to @gelliottmorris

      With COVID, those models *very much* depend on behavior so they are even harder for epi models to be "wrong." It's an exponential dynamic, so yep, the range is huge. The question is were the assumptions justified? You rarely get that from outcome alone given that reflexive range.

      3 replies 0 retweets 3 likes
    5. Adrian Oaks 🦞‏ @FriendOfTheYeti 3 Nov 2020
      Replying to @zeynep @gelliottmorris

      Given Trump's polls in 2016, it's pretty insane to think he had a 1% chance. People with that deficit win all the time. It was a junk model

      1 reply 0 retweets 0 likes
    6. zeynep tufekci‏Verified account @zeynep 3 Nov 2020
      Replying to @FriendOfTheYeti @gelliottmorris

      I do agree those models sucked, but you cannot get that from outcome alone. Any model that did not have correlated shifts taken properly into account sucks for any electoral college modeling.

      2 replies 0 retweets 1 like
    7. G. Elliott Morris‏Verified account @gelliottmorris 3 Nov 2020
      Replying to @zeynep @FriendOfTheYeti

      “Sucks” is just a silly way to hedge against saying “wrong” — or, perhaps better, grossly and dangerously misspecified

      3 replies 0 retweets 3 likes
      zeynep tufekci‏Verified account @zeynep 3 Nov 2020
      Replying to @gelliottmorris @FriendOfTheYeti

      We're not going to finish this here as you note, but I do think moving away from right or wrong as the terminology is important to get to a point where we can 1-communicate what models do; 2-understand they impact outcome; 3-do evaluate them. We do agree they can be evaluated.

      8:15 AM - 3 Nov 2020
      • 4 Likes
      • Sayan Sanyal Rebel Rice
      1 reply 0 retweets 4 likes
        1. John Plasterer‏ @jponline77 3 Nov 2020
          Replying to @zeynep @gelliottmorris @FriendOfTheYeti

          All models are wrong... Some are more wrong than others.

          0 replies 0 retweets 0 likes
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