[MuffinFlavored]

> It probably just recommends a bunch of stuff that is popular at the moment for new users.

I get that, but I feel like it starts with "known safe/neutral" material like cooking/traveling/photography/whatever

How can it detect "hey, this person might like if we introduce softcore porn into their timeline"? Like, do they have softcore porn identified on a scale and they introduce the really "safe" stuff and then gradually crank it up? Why are they presenting softcore porn at all? The Apple App Store is cool with that ToC wise?

[bluefirebrand]

I think you're overcomplicating it.

It's not trying to start with "safe" stuff, it's not trying to "gently introduce" softcore porn.

It's going "This video got a billion views in the last 30 minutes, people must love it, let's keep amplifying it to any account that hasn't explicitly rejected this category of content"

Presumably blank slate accounts are treated as open to anything, until people start curating.

[MuffinFlavored]

during the curation process, how does it start to slowly introduce sex workers? because when I was on TikTok, it was a non-zero amount of the content

[libraryatnight]

At the risk of going down a rabbit hole for no real reason, I don't use tiktok but when I speak to those that do I've not yet heard this softcore porn/sex worker thing.

For example, in my mind, not all ASMR content might lead to sexualized recommendations, but a girl in a bikini top with cat ears doing ASMR might generate both recommendations for ASMR and other more cam-girl like content. So I guess my question is, when you're starting off in tiktok seeing cooking videos, do you trend towards ones that feature 'sexier' hosts? They might not be sex workers to you, but they might be making tiktok think you're interested.

Also, what does tiktok know about you to start? What info do you have to give it to start an account?

[MuffinFlavored]

so you agree that tiktok is able to classify "cooking videos" and "cooking videos with slightly sexualized hosts"? and that they "willingly" "try to push in recommendations" posts with higher "sexuality" attached content?

[libraryatnight]

No, again, my assumption is that the user would trend towards that content. You don't need to push people towards it if you have a nuanced enough profile of each video.

(all things made up for this example)

cookinglady39 does a beach bbq recipe tiktok, in a bathing suit. You watch it. They give you another cookinglady39 video where she's back in the kitchen, you skip it, they give you a new cooking host also female, also dressed in summer attire cooking outside. You watch til the end. It gives you a man cooking outside, you skip. Nothing you've seen so far has been sexual, but tiktok is probably picking up on some trends that might lead them to give you more and more things done by women, then women in a certain setting, dressed a certain way and so on.

[spullara]

TikTok gives you the content you enjoy. When someone complains about TikTok content I basically assume they don't understand how good the algorithm is and that you just like that kind of stuff. I don't care whether you do or not but TikTok thinks you do because of the feedback you are giving the app. I mean, you clicked their profile and followed their links all the way to onlyfans. They have to assume you like it.

[nemothekid]

I think you are anthropomorphizing the algorithm. The algorithim likely isn't ranking sexuality. It just knows people really love this content.

[brookst]

You’re kind of outing yourself here.

All it’s doing is giving you more of what you show the most interest in.

[Bjartr]

Assuming we're starting with a blank slate, and a heteronormative male user that would happen to enjoy consuming that content on TikTok:

In the initial set of recommendations based only on overall popularity, there might be a video that's popular that incidentally contains a pretty woman. If the user skips most videos after barely a few seconds, but watches that one fully 3 times through, then the recommendation engine probably looks at users it does know more about that exhibit similar behavior and have higher engagement. It will then recommend videos that those users would probably watch a lot. Now the recommendations are shifted in the direction from "generally popular" to "contains pretty women". You repeat this enough times and the user ends up navigating the space of recommendations until they're maximally engaged (in theory). That means they might end up at softcore porn. Goodness knows that porn is popular if nothing else.

The recommendation engine doesn't even have to know anything about the content of the video. Just know what already high-engagement users that watched that video a lot also watched a lot.

That's at it's most basic really, I'm sure there's additional cleverness on top in practice.

[oogali]

So, in the old days, if you fall asleep in front of the TV you might have some weird infomercial-fueled dreams. But they’re purged when you wake up.

Now, if you fall asleep in front of your phone screen, it takes days or weeks to shake out that mistake?

[Bjartr]

Maybe, or maybe the system is good enough to low weight or completely discount hours long periods of non interaction.

[bluefirebrand]

My guess is that there is no "slowly introducing" anything.

It just sees that content made by sex workers is popular and puts it in your feed.

[posterboy]

The point of the original poster was that those videos have zero views or low rating - not popular by any means - and they appear out of place in the stream.

Youtube does it too, and my best guess is that it is a form of supervised training and the real question is who's being trained.