Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Twitter's Recommendation Algorithm

blog.twitter.com

Post reply on HN
Print view View original

971–980 of 1001 posts

Re: Twitter's Recommendation Algorithm

#971

Post by amykyta »

nonethewiser wrote: post #685
qbasic_forever wrote: post #532

Earlier quoted context omitted.

Yes that weekend everyone started seeing Elon's tweets in their timelines: https://www.theverge.com/2023/2/14/23600358/elon-musk-tweets... You seem weirdly protective of Elon fyi

I’m pretty neutral on musk. His fanboys are crazy but by and large they aren’t here so there isn’t much opportunity to challenge them. So much has been concluded about him here without any evidence, instead grounding it in the premise that he’s rotten.

Premise? The guy spews the most vile stuff and russian propaganda. There is more than premise to say he’s a piece of shit.

Re: Twitter's Recommendation Algorithm

#972

Post by Szpadel »

toxik wrote: post #867
koolba wrote: post #90

It's reassuring to know that billion dollar tech companies write CI exactly like I do: https://github.com/twitter/the-algorithm/blob/main/ci/ci.sh Permalink: https://github.com/twitter/the-algorithm/blob/7f90d0ca342b92...

I can code golf that script #!/bin/true Bam.

empty file will return 0 as well

Re: Twitter's Recommendation Algorithm

#973

Post by tlholaday »

slim wrote: post #768
db48x wrote: post #551

Earlier quoted context omitted.

Do you think the code looked like that prior to Elon's purchase? I suspect that there was another name there before. Separately, which of these groups do you think that they use as a control?

I don't think so. If the token was "author_is_jake" for example, it would have changed to "author_is_ceo" on second pass

Our old friend Singleton looks up from the bench, hope in their eyes.

Re: Twitter's Recommendation Algorithm

#974

Post by woolion »

So, the day after the headline that Twitter is artificially promoting polarizing political voices, Twitter open-sources their algorithm!

What does the commit history say? There are 3 commits, like a very very real programming project. The issues and pull requests show how much people are fooled by this very transparent move.

So this is an obvious attempt at a digital potemkin village, that like the real one, poorly succeeds in hiding the truth. Elon does not not want to upset the apple cart (political economical or ideological) but make his followers believe in it, and so we get this. Great spectacle, if that's what you're interested in.

Re: Twitter's Recommendation Algorithm

#976

Post by pessimizer »

tric wrote: post #11

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…

If anybody is actually reading this thread, it looks like twitter is using "author_is_democrat" and "author_is_republican" to evaluate "Community Notes."

As with all of the media outlets that elevate these two private clubs into the arbiters of truth, votes for Community Notes have to be relatively balanced between the two parties. Bipartisanship is a trash metric for determining truth, but absolutely none of the people raging at Musk in this thread would disagree with it.

Re: Twitter's Recommendation Algorithm

#977

Post by wizzwizz4 »

bitshiftfaced wrote: post #709
phailhaus wrote: post #568

Earlier quoted context omitted.

Couple problems: 1. Actively supplying negative feedback is sometimes hidden behind secondary menus, making it much higher friction compared to just...scrolling past. So most users don't spend the effort. Even with a dislike button, it's unclear what the system is learning. It can't know that I don't like this particular video because it's a conspiracy theory, and to stop showing me those. These platforms often don't…

Eh, 1 is sort of why I see implicit negative feedback as more useful here. Namely, tracking the duration a user is probably giving their attention to a given item, weighted in accordance with how long you'd expect someone to give their attention to an item based on how long it is. For example, I might see a some specific word or pattern of words in a tweet and quickly skip to the next one. That's very low friction bu…

> Namely, tracking the duration a user is probably giving their attention to a given item,

I pay a lot of attention to classes of things I don't want to see at all.

Re: Twitter's Recommendation Algorithm

#978

Post by emehrkay »

tric wrote: post #11

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…

why arent these strings constants?
Post reply on HN