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Twitter's Recommendation Algorithm

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Re: Twitter's Recommendation Algorithm

#401

Post by ryzvonusef »

suddenclarity wrote: post #391
ryzvonusef wrote: post #304

Earlier quoted context omitted.

Some more strange quirks: https://twitter.com/Ben_Cary_/status/1641893540614623258 > Twitter use to rank posts higher for those who had more followers/less people they follow > They are removing that as of today but kinda interesting that someone with 10k/10k followers would get less reach than if they had 10k followers and only followed 6k

Might be a language barrier from my side but it doesn't really sound like a "strange quirk" but rather a wise decision. Following people to get followers is one of the oldest spam methods on social media. It's not surprising that they would reduce the reach of accounts using those methods.

good point! "interesting insight" might have been a better phrase. i am just skimming twitter to get some scoops on the algo release

Re: Twitter's Recommendation Algorithm

#402

Post by nonethewiser »

anigbrowl wrote: post #161
sillysaurusx wrote: post #102

Say what you will about Elon, but this wouldn't have happened without him. Thanks! And thank you to everyone at Twitter who helped organize this release. Open sourcing something like this is no small effort.

I am not sure about that. Twitter has open sourced a lot of stuff in the past. There were certainly people there who would run the site as a nonprofit public service if they had the choice.

Well, they didn’t

Re: Twitter's Recommendation Algorithm

#403

Post by suddenclarity »

timeon wrote: post #227
joeyh wrote: post #165

Earlier quoted context omitted.

Mastodon is conveniently also AGPL...

On reason I use Mastodon is that there is just chronological timeline. Quick scroll and you are done. Bad for advertising platform - good for user.

Twitter also has a chronological timeline nowadays?

Re: Twitter's Recommendation Algorithm

#404

Post by furyofantares »

mseepgood wrote: post #273
montag wrote: post #236

Earlier quoted context omitted.

Elon is addressing this in the Twitter Space right now. "It definitely shouldn't be dividing people into Republican and Democrats; that makes no sense[...] you've identified something we should be getting rid of right away."

Does it make sense to divide people into Elon and not Elon?

It's not that uncommon to filter analytics based on how much money a user has spent on the platform.

Re: Twitter's Recommendation Algorithm

#405

Post by nonethewiser »

kayodelycaon wrote: post #162
zachnwhite wrote: post #118

Earlier quoted context omitted.

--

The importance of Twitter was it being the primary posting location for a lot of things. A number of the artists and other creatives I know have gotten absolutely gutted by this.

By open sourcing the algorithm? Or what?

Re: Twitter's Recommendation Algorithm

#406

Post by gspencley »

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...

It has been my personal experience, over 25 years in the industry, that often times the bigger the company the worse the code.

It's not an absolute rule, I've certainly inherited projects in a consulting capacity that were written by small teams and were atrocious. But more often than not, a small team working for a small company has fewer of the internal "forces" that incur "technical debt."

Those forces are things like

- Silo'd teams working on a common code base in parallel but never talking to each other, thus duplicating code and having wildly different conventions

- Layers of middle management each with different management styles, leading to inconsistency and product-wide short-cuts

- Dealing with sudden success-induced scalability disasters that result in bandaid solutions

- More employee churn which means that the way we did things yesterday is not the way we're doing things today because someone new is in charge ... more inconsistency in code and software decisions

- More "old code." Companies very rarely do rewrites and when they do they're often failures. So the bigger the company, the more "legacy" spaghetti code typically because you don't fix what isn't broken (especially when the entire system is broken because it's one big giant mess that no one understands and yet somehow it actually works ... as long as we don't breathe on it or get a sudden surge of new account sign-ups).

Re: Twitter's Recommendation Algorithm

#407

Post by correlator »

daveguy wrote: post #112
meghan_rain wrote: post #106

Earlier quoted context omitted.

So why did they opensource it?

So they could pretend to be open. It's the "Open"AI model. Open-washing?

There is clearly a lot of information to share. It's worth considering this could be step 1 of n as opposed to assuming the worst possible intention.

Re: Twitter's Recommendation Algorithm

#408

Post by Mordisquitos »

guelo wrote: post #357
misiti3780 wrote: post #309

Earlier quoted context omitted.

[flagged]

Any time a billionaire buys a media company it's bad for the health of democracy.

Not necessarily. What if the media company was bad for the health of democracy, and the billionaire's incompetence destroys the company's social standing and thus its ability to do more damage (even in the billionaire's own interests)?

Re: Twitter's Recommendation Algorithm

#409

Post by lenzm »

etc_passwd wrote: post #222

Democrats / Republicans looks like it was added outside of SDLC [1]. This order without those features is sorted, likely by a linter, suggesting Elon and Vits are properly implemented, and Democrats/Republicans was just inserted alongside the Elon feature, perhaps just for this extract. Sorting it now results in a different order than the commit. [1]: https://github.com/twitter/the-algorithm/blob/7f90d0ca342b92...

Or Elon was the addition, the other 3 are in alpha order.

Re: Twitter's Recommendation Algorithm

#410

Post by raggi »

robopsychology wrote: post #256
jonathanmayer wrote: post #45

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…

[flagged]

class project, 200 students, 1500 LoC each. Time for grading.

there are contexts in which this may be well practiced.

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