They don't do that though. It's count (a la Twitter trending) then vet (via human) THEN algorithmically predict clickability.
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Replying to @zeynep @jonathanstray
What you are shown is what surfaced, survived vetting, and then algorithm thought you'd click on. More filter bubble.
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Replying to @zeynep @jonathanstray
In Turkey, Twitter trending is one way dissidents can break into national agenda. No chance on Facebook because of algo.
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Replying to @zeynep
1) Twitter trending is a complex algo too. 2) I'd expect "clickable" and "popular" to be very correlated. 3) Still beats a dictator.
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Replying to @jonathanstray @zeynep
I don’t see a major difference between P(click) and total clicks (i.e. “top")
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Replying to @gilgul @jonathanstray
I think Facebook trending is a minor part of site, but any chance that it would balance the feed is .. nope.
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I see difference. If I clicked on
#blacklivesmatter
before, I get story on FB. Otherwise no. Twitter: you see anyway.3 replies 0 retweets 1 like -
Replying to @zeynep @jonathanstray
from our work on FB trends - the only form of personalization seemed to be a re-sort of the same list
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Replying to @gilgul @jonathanstray
There is space for 3-4—ranking is everything. (Yes, you can theoretically scroll the way you can see Google page 83).
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it's all guesses, but what if the diffs in trending come from different parts of population using platforms?
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I'm trying to tell everyone we are not guessing anymore, we have confirmation it's personalized p(click)
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knowing the name of the dep variable doesn't tell us anything about how it's constructed or modeled
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No, but knowing it's personalized & predicts clickthrough tell us a lot about where it will go.
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End of conversation
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