I don't understand why we're limited to one graduate student here when physicists are publishing papers with 5000+ authors BUT. Yes, a reasonable sized team plus past data from social media platforms plus a year or so. You'd have a good start.
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For example: prevalence of exposure to RU-originated memes to voting (voter records are public). Shift in narrative (sentiment analysis of a true random sample) as related to exposure (obviously confounds with algorithm plus self-selection but I've seen papers that get at this).
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Social media data may have natural experiments (when Facebook was testing what kind of news to promote: were there comparable groups we can test effects on?). Interaction between liking an RU-page and downstreat impact. Then impact of downgrading of content from liked pages. etc.
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(Lessened likelihood of voting: among left side of the spectrum, obviously). etc. There is no shortage of stuff to look for.
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Replying to @zeynep @BrendanNyhan
That's not where you and I have a difference of opinion. We're arguing about the scale and magnitude of the impacts. I think the magnitude was small, maybe very small. You've claimed it was medium or large. I'm asking you to propose a way to test whether it was small or large.
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Replying to @NateSilver538 @BrendanNyhan
So, to define small or big. It's a close election. I'd say if plausibly close to winner-loser difference, that's important enough. Still would be small in terms of scale. FB has impressive research published in Nature on voter-encouragement, do it in reverse!
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Replying to @zeynep @BrendanNyhan
OK, then I'd say that the Russian shitposts are not enough to have changed the outcome (which would have required a net shift of ~0.8 percentage points toward Clinton). I'd also consider that to be a pretty *large* effect, as these things go.
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Replying to @NateSilver538 @BrendanNyhan
Brendan and I disagree on how applicable it is but I especially like the follow-up to the Nature paper. This is an impressive example of what you can do with a well-designed study and Facebook data. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0173851 …
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I spent much of 2016 embedded in these networks online, because I had a hunch (lol, from Turkey). I didn't collect big data systematically because I had a hunch and was busy but I watched this. I think people are underestimating how widespread and viral Russian shitposts went. +
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That said, the most useful part of this for me is identifying the mechanism which shows how broken US politics has become. So that's the correct focus, and I think RU outrage threatens to overshadow the fact that the patient is quite ill.
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(The Nature paper, by the way. I think the second one is more impressive in finding because methods are even tighter, learning from the first. https://www.nature.com/articles/nature11421 …)
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