
How YouTube recommendations work [pdf] - praving5
http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/45530.pdf
======
doh
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).

~~~
JoshTriplett
I've found that the YouTube recommendations do a good job of picking a "next"
video to watch, but an exceptionally poor job of constructing the front page.

If I watch "Some Video (part 1)", the recommendations reliably pick "Some
Video (part 2)" next, with the other parts as the other related videos and
similar content further down. If I watch a random video from a particular
channel, the recommendations show more videos from that channel. If I watch a
video of a particular game or a reaction to a given episode of a show, the
recommendations show more videos of that game or more reactions to that same
episode. If I listen to music by a particular artist, the recommendations show
more music by that artist.

On the other hand, the front page consistently shows me 1) old videos I've
already seen, 2) collections of highly viewed content that I have no interest
in _even if I 've already hit the "not interested" X on it_, and 3) popular
videos by channels I already subscribe to (I don't want to know what's
_popular_ , I want to know what's _new_.).

~~~
doh
They do a semi good job with related videos. But even those go south quickly
when you go through couple of them.

~~~
posterboy
exactly

> If I listen to music by a particular artist, the recommendations show more
> music by that artist.

I've had disappointing experiences of that, where the recommendations try to
know what I'd like even better.

------
ebbv
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.

------
kaffeemitsahne
I'd rather know how to turn them off.

~~~
JoshTriplett
Bookmark and visit
[https://www.youtube.com/feed/subscriptions](https://www.youtube.com/feed/subscriptions)
directly, and never visit the front page.

------
jaypaulynice
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-...](https://www.linkedin.com/pulse/beating-youtubes-ads-machine-jay-
paulynice?trk=prof-post)

------
utefan001
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
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
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.

------
chirau
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?

------
oneloop
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
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
For some reason I just assumed that all the more "serious research" was done
in California and completely forgot about DeepMind.

~~~
doh
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
Thanks buddy. I will have to investigate their team and work first, but then I
might apply. Crazy!

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

------
hk__2
Previous discussion:
[https://news.ycombinator.com/item?id=12426064](https://news.ycombinator.com/item?id=12426064)

------
cube00
I can't wait until they start pumping video frames into the image search or
whatever service produces those suggestions for Allo message replies.

------
jepler
poorly.

~~~
oneloop
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.

