5 ms·

How YouTube recommendations work [pdf]

81 points by praving5 10y ago

jepler 10y ago
poorly.
- oneloop 10y ago
  Why do you say that? What they recommend rarely is what I end up watching, but it's usually ballpark correct. So much of what motivates your daily YouTube viewings is externally, so there's only such much you can do. They are aware of this, > Historical user behavior on YouTube is inherently difficult to predict due to sparsity and a variety of unobservable external factors.
kaffeemitsahne 10y ago
I'd rather know how to turn them off.
- JoshTriplett 10y ago
  Bookmark and visit https://www.youtube.com/feed/subscriptions https://www.youtube.com/feed/subscriptions directly, and never visit the front page.
- clydethefrog 10y ago
  There is an extension called Video Blocker. I filtered out most of the horrible channels that kept popping up.
- Perixoog 10y ago
  https://youtube.adblockplus.me/ https://youtube.adblockplus.me/
utefan001 10y ago
If you are a parent, remember that YouTube results and suggestions can sometimes be rather "suggestive". All society needs some baseline of a moral code and an algorithm doesn't understand that. Imagine if your child asked an adult neighhbor about the movie "beaches" and they responded with the same answers YouTube does. Go ahead search beaches. Or Beach, or vine.
- ZeroGravitas 10y ago
  I just tried this, and my first four results were for the Bette Midler film. The rest are about beaches (most dangerous, weird things found on beaches, top 5 beaches in Brazil etc) What is striking, and I've noticed this before on YouTube, is that the thumbnails all feature nearly nude women. You'd perhaps expect this to happen randomly for beach related videos, but I've noticed that if there even a fleeting bit of nudity in a film trailer or similar, it seems to end up in the thumbnail. Does a human scan through and choose that moment, based on trying to maximise clicks? Or does an algorithm try random frames and then keep the ones that are click baitiest?
  - sesqu 10y ago
    That's a human doing it. The algorithm just picks a timestamp to screenshot, and before people were allowed to choose their own thumbnails, they would put a single-frame picture at the timestamp the algorithm was expepected to use.
oneloop 10y ago
This is super interesting. How would I go about working with these guys, considering that they're in Palo Alto and I'm in London? I understand there's a bunch of hops you have to jump through in terms of visas, but I've never really looked into it.
- modeless 10y ago
  These guys may be based in California but Google has a London office, and if you want to work on deep learning then Google DeepMind is the obvious place to go and they're based in London as well.
  - oneloop 10y ago
    For some reason I just assumed that all the more "serious research" was done in California and completely forgot about DeepMind.
    - doh 10y ago
      Actually a significant portion of the tech team (for instance Content ID) is based in Zurich, not in San Bruno. Check out their jobs page [0]. You don't need a friend to recommend you, but it would be great if you find somebody on a team that you are interested to join that would root for you. [0] https://www.google.com/about/careers/locations/zurich/ https://www.google.com/about/careers/locations/zurich/
      - oneloop 10y ago
        Thanks buddy. I will have to investigate their team and work first, but then I might apply. Crazy!
doh 10y ago
There are, I believe, three main reasons why the recommendations are so poor on YouTube: a) YouTube doesn't know anything about the content itself, can only use metadata b) The algorithm itself is biased towards creators that post often and keep users hook the longest, which is almost always vlogers (ask any animator what they think of YouTube) c) Many recommendations systems today create many buckets and once you watch something from one bucket (you show your intent), the algorithm will focus on that bucket only. (You can see it working extremely poorly on Amazon that tries to sell you a fridge after you just bought a fridge). It's very hard to build a great recommendation system (look at Spotify's Discover weekly), but because this is 101 of any machine learning course, it's the primary thing that companies refuse to outsource (I build company around it, failed badly).
- eanzenberg 10y ago
  a) they really don't need to know the content, they can infer most of the content by 'who' watches and how much, aka collaborative filtering. b) Shouldn't bias towards who "posts often" esp if the videos are shit. "Hooked the longest" would be ranked highly if you get hooked like the 'hooked users', makes sense? c) those are poor systems, and actually, I think amazon has one of the much better rec systems. Youtube has one of the worst. Just today their 4th ranked vid for me was the 2 hr long 9/11/2001 broadcast. Wat? Then, they never boost new videos of a channel I subscribe to and have seen every video of theirs over the last 3 months. I literally have to check the channel most recent vid list daily to see if I missed something. I think youtube's weak recommender system is more a result of them having a hammer(deep learning) and seeing every problem as a nail.
  - doh 10y ago
    a) That's the general problem. If you are being encapsulated by the algorithm, there is no way out of the bubble so it doesn't help at the end that they use collaborative filtering, because majority of people ends up watching the same things. b) They chose the metric that made the most business sense. That's why if you spend 6 months working on your video and somebody else produces one video a day, you'll never show up anywhere close to top of the suggested videos. c) Agree. Amazon has one of the better ones, but it's still terrible. You hit the nail on its head with your assumption. This is in general Google's approach. But even with deep learning, the system is heavily biased, intentionally.
cube00 10y ago
I can't wait until they start pumping video frames into the image search or whatever service produces those suggestions for Allo message replies.
chirau 10y ago
What are the methods in ML and predictive modelling that are used to counter 'bucketing'. As much as it is necessary for product creators to land us in groups by behavior, i think it is also necessary to have counter techniques to eventually split those groups and create new ones, no?
ebbv 10y ago
I was just talking about how terrible Youtube's recommendations are with my brother today and I realize this idea is naive but I think it would work better than the current machine language system: - Gather up all the channels that are followed by channels that I follow and/or have liked videos on. - Recommend me videos from those channels. I'm pretty sure in my case this would be much better results than what I currently get shown at any given time.
jaypaulynice 10y ago
Very funny...I wrote an article about how someone could beat youtube's ads machine a few days ago... https://www.linkedin.com/pulse/beating-youtubes-ads-machine-jay-paulynice?trk=prof-post https://www.linkedin.com/pulse/beating-youtubes-ads-machine-...
hk__2 10y ago
Previous discussion: https://news.ycombinator.com/item?id=12426064 https://news.ycombinator.com/item?id=12426064
Siecje 10y ago
YouTube keeps videos I've seen in my recommendations. For years.
deleted 10y ago
[deleted]

81 points by praving5 10y ago

jepler 10y ago

poorly.

oneloop 10y ago
Why do you say that? What they recommend rarely is what I end up watching, but it's usually ballpark correct. So much of what motivates your daily YouTube viewings is externally, so there's only such much you can do. They are aware of this, > Historical user behavior on YouTube is inherently difficult to predict due to sparsity and a variety of unobservable external factors.

kaffeemitsahne 10y ago

I'd rather know how to turn them off.

JoshTriplett 10y ago
Bookmark and visit https://www.youtube.com/feed/subscriptions https://www.youtube.com/feed/subscriptions directly, and never visit the front page.
clydethefrog 10y ago
There is an extension called Video Blocker. I filtered out most of the horrible channels that kept popping up.
Perixoog 10y ago
https://youtube.adblockplus.me/ https://youtube.adblockplus.me/

utefan001 10y ago

If you are a parent, remember that YouTube results and suggestions can sometimes be rather "suggestive". All society needs some baseline of a moral code and an algorithm doesn't understand that. Imagine if your child asked an adult neighhbor about the movie "beaches" and they responded with the same answers YouTube does. Go ahead search beaches. Or Beach, or vine.

ZeroGravitas 10y ago
I just tried this, and my first four results were for the Bette Midler film. The rest are about beaches (most dangerous, weird things found on beaches, top 5 beaches in Brazil etc) What is striking, and I've noticed this before on YouTube, is that the thumbnails all feature nearly nude women. You'd perhaps expect this to happen randomly for beach related videos, but I've noticed that if there even a fleeting bit of nudity in a film trailer or similar, it seems to end up in the thumbnail. Does a human scan through and choose that moment, based on trying to maximise clicks? Or does an algorithm try random frames and then keep the ones that are click baitiest?
- sesqu 10y ago
  That's a human doing it. The algorithm just picks a timestamp to screenshot, and before people were allowed to choose their own thumbnails, they would put a single-frame picture at the timestamp the algorithm was expepected to use.

oneloop 10y ago

This is super interesting. How would I go about working with these guys, considering that they're in Palo Alto and I'm in London? I understand there's a bunch of hops you have to jump through in terms of visas, but I've never really looked into it.

modeless 10y ago
These guys may be based in California but Google has a London office, and if you want to work on deep learning then Google DeepMind is the obvious place to go and they're based in London as well.
- oneloop 10y ago
  For some reason I just assumed that all the more "serious research" was done in California and completely forgot about DeepMind.
  - doh 10y ago
    Actually a significant portion of the tech team (for instance Content ID) is based in Zurich, not in San Bruno. Check out their jobs page [0]. You don't need a friend to recommend you, but it would be great if you find somebody on a team that you are interested to join that would root for you. [0] https://www.google.com/about/careers/locations/zurich/ https://www.google.com/about/careers/locations/zurich/
    - oneloop 10y ago
      Thanks buddy. I will have to investigate their team and work first, but then I might apply. Crazy!

doh 10y ago

There are, I believe, three main reasons why the recommendations are so poor on YouTube: a) YouTube doesn't know anything about the content itself, can only use metadata b) The algorithm itself is biased towards creators that post often and keep users hook the longest, which is almost always vlogers (ask any animator what they think of YouTube) c) Many recommendations systems today create many buckets and once you watch something from one bucket (you show your intent), the algorithm will focus on that bucket only. (You can see it working extremely poorly on Amazon that tries to sell you a fridge after you just bought a fridge). It's very hard to build a great recommendation system (look at Spotify's Discover weekly), but because this is 101 of any machine learning course, it's the primary thing that companies refuse to outsource (I build company around it, failed badly).

eanzenberg 10y ago
a) they really don't need to know the content, they can infer most of the content by 'who' watches and how much, aka collaborative filtering. b) Shouldn't bias towards who "posts often" esp if the videos are shit. "Hooked the longest" would be ranked highly if you get hooked like the 'hooked users', makes sense? c) those are poor systems, and actually, I think amazon has one of the much better rec systems. Youtube has one of the worst. Just today their 4th ranked vid for me was the 2 hr long 9/11/2001 broadcast. Wat? Then, they never boost new videos of a channel I subscribe to and have seen every video of theirs over the last 3 months. I literally have to check the channel most recent vid list daily to see if I missed something. I think youtube's weak recommender system is more a result of them having a hammer(deep learning) and seeing every problem as a nail.
- doh 10y ago
  a) That's the general problem. If you are being encapsulated by the algorithm, there is no way out of the bubble so it doesn't help at the end that they use collaborative filtering, because majority of people ends up watching the same things. b) They chose the metric that made the most business sense. That's why if you spend 6 months working on your video and somebody else produces one video a day, you'll never show up anywhere close to top of the suggested videos. c) Agree. Amazon has one of the better ones, but it's still terrible. You hit the nail on its head with your assumption. This is in general Google's approach. But even with deep learning, the system is heavily biased, intentionally.

cube00 10y ago

I can't wait until they start pumping video frames into the image search or whatever service produces those suggestions for Allo message replies.

chirau 10y ago

What are the methods in ML and predictive modelling that are used to counter 'bucketing'. As much as it is necessary for product creators to land us in groups by behavior, i think it is also necessary to have counter techniques to eventually split those groups and create new ones, no?

ebbv 10y ago

I was just talking about how terrible Youtube's recommendations are with my brother today and I realize this idea is naive but I think it would work better than the current machine language system: - Gather up all the channels that are followed by channels that I follow and/or have liked videos on. - Recommend me videos from those channels. I'm pretty sure in my case this would be much better results than what I currently get shown at any given time.

jaypaulynice 10y ago

Very funny...I wrote an article about how someone could beat youtube's ads machine a few days ago... https://www.linkedin.com/pulse/beating-youtubes-ads-machine-jay-paulynice?trk=prof-post https://www.linkedin.com/pulse/beating-youtubes-ads-machine-...

hk__2 10y ago

Previous discussion: https://news.ycombinator.com/item?id=12426064 https://news.ycombinator.com/item?id=12426064

Siecje 10y ago

YouTube keeps videos I've seen in my recommendations. For years.

deleted 10y ago

[deleted]