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Comment by abc-xyz | Hacker News Reader

TikTok’s recommendation system is absurdly overrated.

I tried to make an account where I only watched (in full length)/searched for/liked videos of a specific gender/race/age group.. yet even after liking over a hundred videos, then 100% of the videos they suggested to me were the wrong gender/race/age group. YouTube on the other hand is capable of recommending the correct videos after watching just a couple. Instagram’s recommendations are also far more accurate (although I dislike the fact that Instagram mostly recommend popular users).

It’s very easy (and shouldn’t take long) to conduct this experiment, just make sure that the race you target doesn’t represent the majority of the users in your proximity. For instance, if you’re in Norway then try to get TikTok to recommend Asian girls aged 20-35.. sounds like it should be easy, right?

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This seems like an unusual use case. Surely a recommendation system should try to find content that matches the users interests. I'm not sure why anyone would want a recommendation system that looks for age/gender/race as that seems fairly irrelevant to interesting content.

I think the intention behind the OP’s post was to test how quickly you could steer the algorithm in a very specific direction.

Its such a shame that Tiktok with its massive teenage userbase doesn't have youtube's infamous recommendation system which inadvertently creates pedophilic wormholes.

I’d say there are countless of valid use cases where this is relevant. Maybe you normally live in (or plan to travel to, or just curious about) X country but TikTok is incapable of understanding you’re only interested in videos from there. Maybe you enjoy watching 20-something year old Asian girls dance, maybe you enjoy watching 20-something white guys skateboarding, maybe you enjoy watching guys with sixpack exercise, maybe you enjoy watching party/club videos, maybe you enjoy watching people cook cakes, etc.

YouTube and Instagram is easily capable of recommending whatever content you show interest in.. TikTok on the other hand feels like the reddit’s /r/popular experience which simply looks at your location and recommend a list of random stuff that people in same area have shown interest in (and completely fail to integrate your interests into this feed). I’m not saying there’s anything wrong with that, but all this hype about their algorithm makes no sense.

If sorting by gender/phenotype/age is your squee, you might have better luck with NSFW sites.

Are you implying that the only valid use case for liking specific types of videos is sexual gratification?

No. I'm stating that if gender/phenotype/age constitutes your prism, explicit fare is the only form of (one-hand casual) video entertainment coming to mind which explicitly categorises by those axes.

I mean, I heard from a friend, who certainly wasn't involved with making any of the stuff, that that's how such sites operate.

(Today I had some trouble searching for "Micro-abrasive Imperial Lapping Film" until I expanded the acronym. Doesn't Google realise I have a connector tip to polish?)

Surely you can see that, as you are unable to speak every language in the world, yet you understand all media presented to you, that ALL of your media is already implicitly sorted by geography and language?

If e.g. YouTube recommended you the best items from all countries, you'd have a very bad time and would be unable to understand almost all media.

The same applies to age and gender. If you were only recommended items relevant to 90 year olds or 9 year olds, you'd have a very bad time on YouTube etc. Just because you don't notice that your media is implicitly sorted doesn't mean it isn't happening.

In fact, I actively search YouTube to watch things in languages I don't understand for audiences whose demographics I am outside. I passively get enough age-appropriate comprehensible-language content just by living in my own society.

a few examples:

https://news.ycombinator.com/item?id=23640033 (9 year olds, RU)

https://news.ycombinator.com/item?id=24431001 (CN, IN, RU, US)

https://news.ycombinator.com/item?id=24398456 (JP, SU, US)

https://news.ycombinator.com/item?id=24156310 (caucasian variety)

Now I realise I should seek out 90-year old appropriate programming. Anyone have any hints?

Bonus clip: https://www.youtube.com/watch?v=y2fNVztaC58

Edit: After a quick calculation, I realise I have watched music from 1943: "Blood on the Risers", "Lili Marleen", "Zog Nit Keyn Mol", "Bella Ciao", and "Катюша" are all suitable for 90-year olds to have encountered as young teens.

Well you're an extreme outlier. Typically people want age-appropriate content in a language that they speak, or, which at least has subtitles. As you point out, if this is your preference then you can use search functionalities for this purpose.

I agree I'm an outlier, but will note that young chinese don't seem to mind plenty of english in their lyrics

https://www.youtube.com/watch?v=hHLRFlKPNMA (with subtitles)

and it's not as if 80s europe wasn't full of foreign-language entertainment:

https://www.youtube.com/watch?v=TDOf41Xwrc4 (caveat for US HN'ers: it's a european music video. No blood, two beasts, some breasts.)

(The 80's were big hair and shoulder pads, no matter which side of the iron curtain.)

> I'm not sure why anyone would want a recommendation system that looks for age/gender/race as that seems fairly irrelevant to interesting content

You can't understand how age/gender/race is important for finding relevant content?! These are extremely important, fundamental, attributes that underpin good recommendations. I.e. they're so important that they generally go without saying, and are baked into the corpuses (e.g. your local news site doesn't recommend articles from another country, Disney's streaming service doesn't recommend knitting shows to children, etc)

Would you be happy if your Amazon Prime or Netflix account only showed items that are interesting to people aged {opposite age group to you} in {country on the other side of the world to you} who are {not your gender}?

I think you'd very quickly be surprised at how much media exists in the world and would quickly realise that you're mistaken.

"Algorithm isn't racially discriminatory" is an unusual complaint.

Really?

If somebody tried to sell me a facial recognition system and it matched my face with somebody of the opposite gender and a totally different race, well, I would not buy that system.

We're talking about video/image recognition here, not politics.

The intent of a facial recognition system is to match an individual, surely?

The intent is to match the appearance of their face.

TikTok as a whole is insanely overrated, at least in my opinion. I've really given it multiple tries, hours at a time, but it consistently fails to serve me anything that even remotely entertains me.

My biggest gripe with it is that half of the content appears to be of the "build some tension up by hinting at a certain conclusion of the video, then simply ending the video before it comes to that conclusion and leave the viewer clueless" type, and TikToks famed algorithm seems to be entirely unable to discern that I hate this crap. Maybe it's because I watched some of these fully in the beginning until I understood the pattern. However, afterwards I swiped this kind of video away immediately once I notice the pattern, but the famed algorithm appears to be unable to re-learn that I really, really, really hate this kind of content.

> build some tension up by hinting at a certain conclusion of the video, then simply ending the video before it comes to that conclusion and leave the viewer clueless"

People who expect a neural network to identify stuff like this have drunk WAAAAY too much ai kool-aid.

It's without question aimed at and useful primarily for a young demographic with an extremely short attention span. It's also really hard to create long-form quality content, the short clips remove that pressure, which is exactly what short tweets accomplish (the typical TikTok user is creating absolutely nothing original, they're all directly copying eachother; you have a tiny number of originators, and then everyone else is a clone (a mimic), which is humanity in a nutshell). It's mostly about status battling, young people fighting for some attention, trying to put a stake in the ground to claim status among peers to position themselves. It's why so many of the most popular users live in nice locations, in mansions or otherwise huge very nice homes, they're envied, they're pitching/riding status to a million followers. The sex selling, faux-dance cloning and ass shaking (WAP WAP WAP) that the majority of of the non-celebrity popular users use it for, tells you everything you need to know. It's the same thing that made Snapchat popular, sex always sells. TikTok of course derived from Musical.ly and was popularized first in the US among teenagers. The content that fills up the platform is still similar to what originally made Musical.ly popular.

TikTok is the Kardashian effect brought down to the masses of people, to roll around in. Mimic in just the right way and you too can be Kim for 15 minutes (if your house is big enough and or you're attractive enough, as you have to be able to sell it). TikTok's most popular non-celebrities are pitching exactly the same thing that made the Kardashians so popular, in the exact same way. It's a cultural wasteland, celebrated.

What the hell is anybody going to say in 10-15 seconds that is going to be valuable outside of a quick clip of music and some status pitching (show a big house, shake your ass, take off your shirt, dive into a pool, show seven seconds of a party)? Absolutely nothing. It's the same thing Instagram is mostly used for: status positioning, signaling. There is a reason why the evidence overwhelmingly points to all of this as being unhealthy - it's all built around intentionally amplifying an addictive, desperate aspect of human nature that is a big negative at its extremes (status seeking, narcissism, bullying, social competition, selling sex, all in a swirl together and pumped up).

You are seeing a very different FYP than I just saw on tiktok.com.

Is TikTok a SSCly Scissor Service?

https://slatestarcodex.com/2018/10/30/sort-by-controversial/

TikTok kept trying to show me rich people dancing in their mansions for about 2 days when I first downloaded it (and so: I couldn't understand the hype about it), but hasn't shown me that since. Now I understand the hype.

I, on the other hand, have a totally different experience. I used tik tok for a day and was really frustrated with the not very interesting content, but after explicitly disliking a couple of videos I got an amazingly interesting stream of funny videos from there on out. Given that all the information the algorithm has is rather indirect and negative feedback compared to classic news feeds were you positively select the creators in the beginning and the huge amount of new content that comes to the platform every day, I found the training time rather short and the result really good.

> "build some tension up by hinting at a certain conclusion of the video, then simply ending the video before it comes to that conclusion and leave the viewer clueless"

These videos are certainly pervasive - they are an attempt to trigger reactions to show that you like this content: for example, by getting you to watch through the end of the video, click on the creator's name for follow-up content, checking the comments for clues.

You can understand the videos as an attempt to game the algorithm, and I also think they are playing on themes which humans are genuinely addicted to and find it hard to fully control.

Long click will allow you to 'remove content from this creator' (excuse my translation): that will help.

Have you considered the possibility that this behaviour is not a bug but rather a feature?

Ah yes, the last refuge of the scoundrel.

Two potential issues come to mind when I consider your test through the lens of TikTok:

1. There basically isn't content where the content consists solely of the gender/race/age of those in frame and nothing else (outside of fetishism).

2. People who strictly want to only watch that content aren't very common (outside of fetishism).

So it makes sense why your cohort might not show up on a website that has a much more intolerant stance on NSFW content than Youtube and Instagram.

If we're to believe that TikTok only recommends videos that have been human-tagged (claimed in TFA and in these comments), then it seems even more likely that a video of (your example) east asian women aged 20-35 dancing to music are tagged "dancing", (e.g.) "kpop" and not "east asian" "women" "20-35". And your feed of "dancing" + "kpop" recommendations only incidentally contain the demographic you seek while being oblivious to it.

Just guessing, of course. I have a kneejerk charity response for something when someone on HN says that it's absurdly bad. ;) If only I had this reflex at all times.

This is why TikTok's algorithm is better than YouTube's, in my opinion.

YouTube takes the content you have seen and explicitly shown that you like, and shows you a more extreme version of it. It tends to over-recommend alt-right YouTube, for example.

TikTok takes the content you have seen and implicitly shown that you like, and shows you diverse content that has some of the features you seemed to enjoy, while it learns from that.

If you are looking to fetishise young Asian women, then maybe you are on the wrong type of website (and: maybe you shouldn't do this).

Is it a bug in the algorithm, or a feature of it? If I'm a young Asian woman creator, I also have an interest in whether the algorithm is fetishising my work.

> TikTok takes the content you have seen and implicitly shown that you like, and shows you diverse content that has some of the features you seemed to enjoy, while it learns from that.

In my case the recommendations had nothing to do with what I had liked or shown interest in. It was equivalent to visiting Reddit’s /r/popular, which might appeal to most people, but from an algorithmic perspective then there’s nothing impressive about it. Like I also mentioned in another comment, I think there’s nothing wrong with this approach, I just don’t understand how people can be impressed by it from a technical point of view.

> If you are looking to fetishise young Asian women, then maybe you are on the wrong type of website (and: maybe you shouldn't do this).

I was just trying to conduct the most simple experiment imaginable to see whether it was actually capable of detecting what I showed interest in and do so in a way that I could easily verify the results. What I was looking for in the experiment represent perhaps 20% of the userbase, yet it was still incapable of displaying a single post that matched what I was trying to achieve (because the feed just show what they believe is interesting in your area). I could also have tried to achieve something more complex, like train TikTok to show skateboarding videos (which might represent less than 0.001% of their videos), but I figured I’d try with the easiest thing imaginable first (which it failed at).

And I fail to see why there’s anything wrong with being interested in watching content of people within a certain age group, or gender, or nationality..

If I were a TikTok user then I’d surely hope that they were able to recommend my videos to people that were interested in the kind of content I posted (because that would open up a lot of possibilities, like meeting people with similar interests, selling products, etc.)

So your claim (in response to my point) is that young Asian women who might create content on TikTok want to be fetishised? I don't think so.

Youtube mostly suggests already seen videos, hence i wouldn't classify it as a good recommender. I agree with your comment on instagram.

In general, there are multiple approaches on recommender systems, to name but a few: -suggest content with similar features with what you watched -suggest content that similar users already watched -suggest completely new and/or different content

I haven't used tik tok, but you might fall into category #2 and #3. And to be honest, if i owned such an app i would pursue users to be recommended new and popular content to keep them in the platform.

You just pointed out the exact problem I don't like about YouTube. It assumes you are going to watch based on exactly what you have watched. Which we don't. We want the recommendation system to suggest something different but to our taste. It is not like you are going to have the same meal again and again.

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