511–520 of 1001 posts
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Seems dumb of them. Cost is trivial and their competition that isn’t so politically motivated will have a much further reach. The smart move would be silent on the policy change, pay, and support rival platforms as they can. Instead they will eventually pay and look like they lost.
We’re in a time where ideology trumps revenue for some companies. You know, “Get woke, go broke.”
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Only used for metrics, apparently. [0] /** * These author ID lists are used purely for metrics collection. We track how often we are * serving Tweets from these authors and how often their tweets are being impressed by users. * This helps us validate in our A/B experimentation platform that we do not ship changes * that negatively impacts one group over others. */ [0]: https://github.com/twitter/the-algorithm/blob/7f…
I expect they're tracking the red team/blue team metrics because of the political shitstorm that's been the GOP's assertions they're being silenced by The Algorithm.
Now one side can spew as much disinfo and incitement to violence as it likes, and any algorithm change that prevents this shit from getting amplified will be rejected as bias.
BSaaS = Both Sides as a Service
From https://github.com/twitter/the-algorithm/blob/7f90d0ca342b92... ( "author_is_elon", candidate => candidate .getOrElse(AuthorIdFeature, None).contains(candidate.getOrElse(DDGStatsElonFeature, 0L))), ( "author_is_power_user", candidate => candidate .getOrElse(AuthorIdFeature, None) .exists(candidate.getOrElse(DDGStatsVitsFeature, Set.empty[Long]).contains)), ( "author_is_democrat", candidate => candidate .getOrEls…
Did they not expect people to notice suspicious code like this? Or did they leave this in just so they could hold its removal up as an example of listening to the community?
So as expected, there is exactly nothing that favors posters from one side of the political spectrum. I don't expect that this article will do anything to calm down those who are convinced otherwise though. Well written article, from an engineer's perspective.
From https://github.com/twitter/the-algorithm/blob/7f90d0ca342b92... ( "author_is_elon", candidate => candidate .getOrElse(AuthorIdFeature, None).contains(candidate.getOrElse(DDGStatsElonFeature, 0L))), ( "author_is_power_user", candidate => candidate .getOrElse(AuthorIdFeature, None) .exists(candidate.getOrElse(DDGStatsVitsFeature, Set.empty[Long]).contains)), ( "author_is_democrat", candidate => candidate .getOrEls…
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Only anecdotally. But ever since Musk took over the amount of US political content has significantly increased in particular from the right despite me not living in the US. It's hard to tell whether previously political content was weighted less and Musk has removed those controls or whether they are now weighted higher.
Some of the power users Musk reportedly had boosted are specifically right wing political posters, like catturd2. But then he's also boosted some high profile left leaning politicians, so it's not exclusive. It does mean you're more likely to see right wing American political content either way, which has to be annoying for people outside of the US. https://gizmodo.com/twitter-algorithm-aoc-ben-shapiro-cattur...
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This is (weirdly) common in production ML codebases written by software engineers. Like you, I have no idea why unless it's a memory optimisation (where you count 4+ as many).
Having every column as a boolean (0/1) means you can treat it as a bitmap. As an (entirely fictional) example, imagine if you wanted to get the features of a thread instead of a single tweet. You could do it as a union of all the tweets: threadFeatures = tweet1 | tweet2 | tweet2
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When your visa is on the line, you’ll do anything
Engineers who work at twitter can easily find another job in the US.