Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

TikTok reveals details of how its algorithm works

axios.com

Post reply on HN
Print view View original

141–150 of 190 posts

Re: TikTok reveals details of how its algorithm works

#141

Post by Aromasin »

tshaddox wrote: post #138
jzymbaluk wrote: post #85

Earlier quoted context omitted.

A common comment I see on Tiktok videos is something like "I've finally made it to [niche interest] tiktok", it's something I've experienced myself when the algorithm started showing me videos from the crew on cargo ships as they talk about their favorite ports to dock at, or their experience going through E.G the Panama Canal. I don't know any other platform that emergently figures out that I have an interest in int…

The exact same thing happens for me on YouTube, although I guess YouTube doesn't start with an auto-playing random sequence of videos to quick-start the search for videos you find interesting. Still though, I end up in very odd niches that I never specifically searched for.

One thing I will say is that I feel YouTube doesn't do this to nearly as large of degree as TikTok. YouTube might suggest me videos that are outside my cluster of interests occasionally, but normally only those with a reasonably high view count. They will recommend low view count videos that are within my interests however.

TikTok on the other hand will sometimes show me a video with almost no views, that is completely random, and I actually do like it. I feel like YouTube has gotten slightly stale in that it tries so hard to show me either viral videos or videos it deems to be of my interests, that the content becomes repetitive. In recent months it's become better at it, but still plays it safe with recommendations.

Re: TikTok reveals details of how its algorithm works

#142

Post by jethro_tell »

sbilstein wrote: post #103
undefined1 wrote: post #73

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 n…

I wish I had data on the average length of youtube videos over time. I swear 5 years ago an explainer video or a game review would be less than 5 minutes consistently, which is what I personally want from a platform like youtube, a digestible snack of information. Nowadays career youtubers are often pushing well over 10 minutes which just occupies too much of my time to be worth the distraction.

I used to watch YouTube now it is the place of last resort for any content or explanation because its too slow. I once had to spend 9 minutes watching a video about how to get a tricky gasket out of a spot on my truck. The short answer is that you take a 3/4 inch threaded pipe twist it into the gasket and pull down. The long answer was a 9 minute video. Almost always, when a link takes me you YouTube, I just assume I don't need to know that bad. Its like a recipe site that can't be scrolled or searched.

I really moss when people wrote what they did in little snpits on blogs.

Re: TikTok reveals details of how its algorithm works

#143

Post by PragmaticPulp »

majormajor wrote: post #133
pizza wrote: post #128

Earlier quoted context omitted.

I wish the recommendation algorithm had knobs users could manipulate. eg - show me things that have - reduce the weight of popular channels - don't send me into a political content feedback loop - prefer to show me short videos - show me something wildly outside my tastes every now and then I just got the Youtube Music app and it had very crude music recommendation options. You have to pick from a pre-selected list o…

The biggest problem in user-facing software right now is that product managers assume they + an algorithm can figure out what you want based on behavior, and that you shouldn't have any direct input in that. The best you'll usually see is an "i don't like this" button. Spotify sidesteps some of this by just giving you a bunch of different algorithms feeding different playlists, so at least there are options, but I mi…

> The biggest problem in user-facing software right now is that product managers assume they + an algorithm can figure out what you want based on behavior

Given Tik Tok's success, this appears to be a correct assumption.

For every 1 engineer who wants ten different knobs to use the app like a power user, there are 100 or more regular users who don't want anywhere near that much complexity.

Catering to the power users only makes sense if they're your core market. For most public-facing apps, especially free apps, creating and maintaining power user level controls is far more trouble than it's worth.

Re: TikTok reveals details of how its algorithm works

#144

Post by rvnx »

baddox wrote: post #140
fpgaminer wrote: post #119

Earlier quoted context omitted.

Historically YouTube would downregulate short videos in their algorithms. The cutoff was 10 minutes, if I remember correctly. So the biggest content creators got used to stretching out any video to at least 10 minutes. I think YouTube has relaxed that a bit recently. Which is funny in the greater historical context, because in the early days of YouTube you couldn't upload videos longer than 10 minutes. EDIT: As an as…

I believe the 10 minute thing is because YouTube at some point let you include mid-roll ads if your video was longer than 10 minutes.

Yes the 10 minutes unlock you significant monetization options

Re: TikTok reveals details of how its algorithm works

#145

Post by rvnx »

dannyw wrote: post #40
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.

Bytedance has thousands of the smartest data scientists in China.

Bytedance has thousands of Manual Labor specialists as well.

Using ML it is very easy to tag videos.

Re: TikTok reveals details of how its algorithm works

#146

Post by rvnx »

Jommi wrote: post #131
red_hare wrote: post #127

I find that it takes device into account very interesting. What does me using an iPhone XS vs a Samsung Note vs a generic cheap Android phone say about me? I wonder if ends up being a proxy for income, age, or gender...

oh its 1000% a proxy for income. No doubt about it.

Like Tinder checks your phone model to understand whether or not you are attractive (iPhone users have boost)

Re: TikTok reveals details of how its algorithm works

#147

Post by rurp »

pizza wrote: post #128
sleepydog wrote: post #75

Earlier quoted context omitted.

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.

I wish the recommendation algorithm had knobs users could manipulate. eg - show me things that have - reduce the weight of popular channels - don't send me into a political content feedback loop - prefer to show me short videos - show me something wildly outside my tastes every now and then I just got the Youtube Music app and it had very crude music recommendation options. You have to pick from a pre-selected list o…

I hate the modern software trend of disallowing explicit filtering. On everything from Youtube to Netflix the user is limited to typing in what they want and hoping the algorithm correctly reads their mind. If it doesn't, you're left trying to trick it into searching on what you want or looking for an outside resource where another person has already done the grunt work.

Re: TikTok reveals details of how its algorithm works

#148

Post by tqi »

Devil is in the details, a lot of which seem to have been lost in this explanation. This seems to be mostly a view into their value model (ie prioritize P(Click) * value + P(Heart) * value etc), but the hidden issue arise from the type of content that is likely generate clicks / hearts / long watch times.

Re: TikTok reveals details of how its algorithm works

#149

Post by jassany »

robjan wrote: post #63
ramraj07 wrote: post #55

Earlier quoted context omitted.

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 has the problem that all Google products have: they put you in a filter bubble which you can never get out of. The algorithm also optimises for more "long form" content and it's pretty well known that the optimum video length is around 10 mins.

if you simply erase you watch history that will reset your recommendations, always works.

Re: TikTok reveals details of how its algorithm works

#150

Post by majormajor »

PragmaticPulp wrote: post #143
majormajor wrote: post #133

Earlier quoted context omitted.

The biggest problem in user-facing software right now is that product managers assume they + an algorithm can figure out what you want based on behavior, and that you shouldn't have any direct input in that. The best you'll usually see is an "i don't like this" button. Spotify sidesteps some of this by just giving you a bunch of different algorithms feeding different playlists, so at least there are options, but I mi…

> The biggest problem in user-facing software right now is that product managers assume they + an algorithm can figure out what you want based on behavior Given Tik Tok's success, this appears to be a correct assumption. For every 1 engineer who wants ten different knobs to use the app like a power user, there are 100 or more regular users who don't want anywhere near that much complexity. Catering to the power users…

TikTok appears to let their algorithm do a lot more random walking than other companies. That's in some ways different from power user knobs, but it serves a similar purpose in exploring a broader area instead of assuming they can intuit everything from previously-collected data.

That's an improved default that fits well for their app. But infinite scroll is not the only use case in the world.

This assumption that "what works for [one app] is the path I should follow because that app has been successful" is frustrating and shortsighted.

Post reply on HN