It's disappointing the comments are so obsessed with the political angle to this that there's a total lack of appreciation (or discussion) of opening up the most influential social media platform in the world.
Twitter's Recommendation Algorithm
201–210 of 1001 posts
Re: Twitter's Recommendation Algorithm
#202From 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…
The author_is_elon flag doesn't surprise me, but the two political designators are somewhat shocking. I'd sure like to know what changes based on what Twitter knows about your political affiliation.
It's not that shocking...
Half the people that got promoted on my timeline were perpetually candidates for elections I couldn't vote in, and they _self-identified_ as Republican or Democrat in their own bios, or via the registration of their candidacy...
This is why I exclusively used to use Twitter in the "people I follow only" mode, and simply shut my account down when they pushed harder on the algorithm.
Re: Twitter's Recommendation Algorithm
#203From 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…
I opened this thread just to verify this would be top comment, good job hn
Re: Twitter's Recommendation Algorithm
#204Context: 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…
What did you expect?
I don’t know if the parent’s expectations matter here. This is more about making sure others don’t misunderstand the meaning here.
Re: Twitter's Recommendation Algorithm
#205I generally have a very low opinion of social media platforms, but I did create a Twitter account for the first time after Musk bought the platform.
My conclusion is that it's basically entertainment, with very little of what I'd call high-quality useful information that deserves further examination (unlike a lot of HN posts, in contrast). I also notice something of a Tik-Tok approach to video being implemented, which is not surprising given Tik-Tok's success (and makes one wonder who exactly it is lobbying so hard for a Tik-Tok ban, and whether it's just a commercial competition issue more than anything else).
As far as the recommendation algorithm, it appears to be a siloing setup - look at content of one particular flavor, it gives you more of that flavor. A 'flush settings' or 'forget browsing history' or 'reset to defaults' button would be useful, if probably not what advertisers want in terms of delivering to target audiences. I suppose setting up multiple accounts is something of a solution, although too much effort to be that interesting.
In terms of news reports, it's broader in scope than traditional corporate media outlets, so that's a plus in its favor. Reliability is perhaps similar (i.e. low).
Re: Twitter's Recommendation Algorithm
#206Earlier quoted context omitted.
\* \* 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...
Still smells to high heaven to me. Not the Elon part, I don't really care about that. But collecting metrics about "republican" vs "democrat" sounds like a particularly bad set of priorities at work.
> sounds pretty suspicious.
Sounds toxic to me
Re: Twitter's Recommendation Algorithm
#207You gotta hand it to Elon - he actually did it.
Where is the file containing accounts that are artificially boosted? We can guess what its single line is, but how is it incorporated into the algorithm?
Re: Twitter's Recommendation Algorithm
#208Squashing the commit history before releasing it was an interesting (and completely predictable) decision.
It doesn't seem particularly interesting? I would never make a formerly private repo public without first erasing the history. There's no upside to showing everyone your work in progress and almost unlimited downsides.
Re: Twitter's Recommendation Algorithm
#209I 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...
All in service of 'anti-bias' of course... /s
Re: Twitter's Recommendation Algorithm
#210If Twitter was 'dead' why on earth are we still talking so much about this blue bird site? It looks like once again these lot predicting that he won't open source the algorithm and are going to start eating their words again [0], just like they did around incorrectly predicting Twitter's immediate collapse [1] and will look at the source code anyway and continue to talk about "Twitter" again. If Twitter can open-sour…
Are you kidding me, running a botnet is easier than it has been in years if you're that way inclined. The amount of spam I see has gone way up over the last 6 months.