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TikTok reveals details of how its algorithm works

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Re: TikTok reveals details of how its algorithm works

#71

Post by Kaze404 »

jakear wrote: post #8

It's a (seemingly) pretty simple matter of keeping track of how long someone looks at a video, and optimizing to show them videos they'll spend a long time looking at. It's pretty powerful too, I spend much more time looking at TikTok than any other digital content aggregator (to the extent I had to delete it from my phone). They also do some things like sprinkle in random fresh videos, potentially unrelated to your…

> It's pretty powerful too, I spend much more time looking at TikTok than any other digital content aggregator (to the extent I had to delete it from my phone).

Similar experience here. One night a few months ago my girlfriend and I decided to download it as a joke. We laughed at some videos for a while and went to sleep. A couple months later she'd spend hours upon hours every day looking at it, even foregoing some of her hobbies. Eventually she realized it was too much and also uninstalled it.

Re: TikTok reveals details of how its algorithm works

#72

Post by londons_explore »

benreesman wrote: post #61
disgruntledphd2 wrote: post #45

Earlier quoted context omitted.

I actually think it's got much more to do with the training data. Given that you are watching a video, you need to either swipe away from it, or finish watching it. This provides either a 1 or 0 for the video classification model. The important contrast here is with FB/IG feed where you can scroll aimlessly without engaging, leaving you with perhaps 1 engagement out of 10 (or whatever). The attached doc suggests that…

Dwell is a very powerful ranking signal in a binary classifier. Pairwise association of videos watched by the same user consecutively or even just sampled pairs from their last N videos will get you a video embedding. Pairwise sampling of users who watch the same video to the end will get you a user embedding. Turking category tags will prime the pump for other types of embeddings. These things can be ensembles, stac…

What surprises me is all of what you've said is the way pretty much all recommenders work - YouTube, Facebook, Twitter, etc. will all be doing this.

Yet people don't spend hours per day browsing tweets.

What is it about tiktok which is so much more effective?

Re: TikTok reveals details of how its algorithm works

#73

Post by undefined1 »

TikTok is like a highly compressed version of YouTube.

YouTube incentivizes creators to make artificially long videos, resulting in a huge amount of filler. So you get a lot of videos where you can skip the first 20%+ and not miss anything. The content is buried and spread out.

1 minute of content surrounded by 9 minutes of filler.

TikTok removed those 9 minutes, so it feels very refreshing in that respect. There's no incentive to create filler - just the opposite.

Of course the downside is that there's only so much you can fit into a 60 second package, so you're not going to get a deep dive into anything. But for the kind of content that can be compressed like that, TikTok wins big time.

Re: TikTok reveals details of how its algorithm works

#74

Post by Drew_ »

btilly wrote: post #57
xnx wrote: post #18

Earlier quoted context omitted.

There's so much good meta-data (likes, comments, duration, sound used, views, like/view ratio, skips, loops, subscribes, etc.) that I'd be surprised if they were digging into the contents of the video at all right now.

They claim to be looking at the music in the video and avoiding sending you to another video with the same music.

That would be the "sound used". The music in the video is specified/labeled before upload so there's no need to actually process the sound of the video.

Re: TikTok reveals details of how its algorithm works

#75

Post by sleepydog »

xnx wrote: post #11
jakear wrote: post #8

It's a (seemingly) pretty simple matter of keeping track of how long someone looks at a video, and optimizing to show them videos they'll spend a long time looking at. It's pretty powerful too, I spend much more time looking at TikTok than any other digital content aggregator (to the extent I had to delete it from my phone). They also do some things like sprinkle in random fresh videos, potentially unrelated to your…

I've also found that TikTok does a good job of throwing in unexpected videos to test the waters of what the user is interested in. This diversity is one of my favorite things about it.

I wish youtube was better in this regard. The videos it shows me just keep getting more and more focused on what it knows I'm interested in, to the point that it's boring. I discover new things to watch through reddit instead.

Re: TikTok reveals details of how its algorithm works

#76

Post by Drew_ »

ramraj07 wrote: post #55
xnx wrote: post #9

Earlier quoted context omitted.

More data beats smarter algorithms any day, and TikTok gets a lot of data because its videos are so short and interaction rate so high. There are tons of signals it can use as inputs: How much of a video did you let play before swiping next? How many times did you let the video loop? Did you like? Did you comment? Did you like a comment? Did you click through to the profile? Did you view other videos from the profile…

I don't buy this argument. YouTube ostensibly has a metric ton of information like this and even if tiktok has more training data now, I'm fairly sure their training data in principle was smaller than what YouTube historically had given their decades long presence and their ubiquity in the internet. This is on top of the documented effort by YouTube to perfect their recommendation algorithm using the best ML minds th…

YouTube's recommendations are arguably just as good as TikTok's in my opinion. The only difference is that YouTube places the burden of choice on you while TikTok makes every choice for you.

If you don't quickly find something you'd like to watch on YouTube you're very likely to leave and find something else to entertain you. Meanwhile TikTok is automatically feeding you an infinite source of quick and easy to digest content, all of which you'll probably like to some degree.

YouTube could do something similar and give users an automatic continuous feed (ala a TV channel), but I think YouTube's content is much too longform to work well in this format. This burden of choice problem affects Netflix in the same way which also has superb recommendations.

Re: TikTok reveals details of how its algorithm works

#77

Post by htrp »

srean wrote: post #69
xnx wrote: post #18

Earlier quoted context omitted.

There's so much good meta-data (likes, comments, duration, sound used, views, like/view ratio, skips, loops, subscribes, etc.) that I'd be surprised if they were digging into the contents of the video at all right now.

Almost all of those applies to YouTube, do they not ?

IIRC youtube vids are too long to do any useful feature extraction from the videos.

Re: TikTok reveals details of how its algorithm works

#78

Post by jordache »

rvz wrote: post #68
jordache wrote: post #36

don't see how tiktok is so game changing? How long can one look at random dance videos? What demographic would maintain sustained interest over years? flavor of the month/year?

> flavor of the month/year? Actually, yes. This particular generation will eventually grow out of TikTok like they did with other social networks at their peak of the hype cycle: Snapchat (2014), YikYak (2014), Vine (2015), Shots (2012) and SNOW (2016) etc. TikTok is no different and yet another hype masterpiece for the record books and the news media. The new kids will find another one to replace it and suddenly it…

ha Vine

Re: TikTok reveals details of how its algorithm works

#79

Post by TheJoeMan »

chaotic_mind wrote: post #30

To be fair, the algorithm they told is mostly what we would have perceived, knowing if that is Machine Learning driven. Although, I am quite intrigued what they would be showcasing in their "transparency centers". If they show what extent their data can be utilized. and not simply a simulation of the ML stuff.

I think it's interesting how they took the warnings on creating feedback loop "bubbles" and social media addiction causes and used that as their business model.
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