181–190 of 1001 posts
"Today, the For You timeline consists of 50% In-Network Tweets and 50% Out-of-Network Tweets on average, though this may vary from user to user." I have spent significant effort creating a network and there you go choosing to ignore my efforts by putting in 50% of crap-I-don't-want-to-see. That is why I despise your algorithm.
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\* \* 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. \* From: https://github.com/twitter/the-algorithm/blob/7f90d0ca342b92...
So now engineers working on the algo can ensure their launches won't lower Elon's tweet visibility. Looks like those remaining at Twitter have a knack for corporate survival.
I wonder what the "author_is_elon", "author_is_power_user", "author_is_democrat", and "author_is_republican" labels are for [1]. [1]: https://github.com/twitter/the-algorithm/blob/main/home-mixe...
\* \* 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. \* From: https://github.com/twitter/the-algorithm/blob/7f90d0ca342b92...
Context: I teach at Princeton and study social media and recommendation systems. From a very quick skim of the repositories, this appears to be quite limited transparency. The documentation gives a decent high-level overview of how Tweet recommendation works—no surprises—and the code tracks that roadmap. Those are meaningful positive steps. But the underlying policies and models are almost entirely missing (there are…
Haven't gone through yet, but yeah, if that's the case, all this is, is a glorified framework to plug your own in.. Not exactly what was promised.
Great pull request here which improves the algorithm: https://github.com/twitter/the-algorithm/pull/17
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That would be great (unweighting bluechecks) but they actually plan to go in the other direction: Starting April 15th non-bluechecks won't show up in the "For you" section (the algorithm timeline) at all. Unpaid users are being written completely out of the algo. https://twitter.com/elonmusk/status/1640502698549075972
I believe LeBron James said recently he isn't going to waste his money on a blue checkmark, so it should be interesting to see what stays and what goes.
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I know there's a joke about this regarding his ego and there's certainly some truth in that, however it's also quite believable that after a deployment he might have noticed the popularity of his tweets going down (since he no doubt checks his reach), so I can kind of understand how he might see "republicans", "democrats" and "celebrities_it_makes_sense_to_check_this_with_my_account_as_i_am_a_very_active_user" as cor…
We don't need to speculate on this. It sounds like he did actually fire engineers over his tweets getting less engagement than he wanted. https://www.platformer.news/p/elon-musk-fires-a-top-twitter-...
But, we do have a bit of code that measures metrics on his account, so can we find the bit of code that increases the engagement on his account?
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So they could pretend to be open. It's the "Open"AI model. Open-washing?
This is a very cynical take. They should be commended for publishing recommendation code at all, which no other major social network does.
If we commend them for this we're helping promote and encourage this faux open source virtue signaling