Okay! Keep looking at percent of tweets as a good metric for impact—and doctors should weigh viruses/bacteria as percent of bodymass to decide on impact and not look at how it impacts body/immune system (aka the whole ecology) . Good luck, to you and Dr. Google. ¯\_(ツ)_/¯
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Yes my suggestion is maximal. You can look for bites. There might be natural experiments. Companies have longitudinal data—some of it may eventually be analyzed (if they are not already doing so). We should look back at panels that exist, etc. Weak, easy measures are still weak.
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Their unwillingness to unpack and question the psychological models of behavior they premise their “scientific tests” on is telling
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OK, then give me some other hypothesis that's *actually testable* and that someone (you or me or a smart graduate student out there) could *actually test* (i.e.. the data is available publicly) in a reasonable length of time.
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This is a fantastic thread, and I feel sorry for
@zeynep
End of conversation
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The key criterion is that a hypothesis be easy to test even if it has almost no explanatory power. Er.
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This also goes to the “repression of otherwise-Hillary-voters”. How do you “measure” repression without a control group?
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