Ask HN: Why is making a good recommendation system for YouTube hard?

Re:Ask HN: Why is making a good recommendation system for Yo... by cameldrv on Wednesday December 23, 2020 @12:40PM (#25520000)

You can make a great recommendation algorithm, certainly better than YouTube's, if you use a different criteria for success. YouTube's criteria is to recommend whatever causes you to watch a lot of YouTube.

It could be that most people's goal in life is not to watch the maximum amount of YouTube.

One thing I've wanted since I saw a prototype Joe Edelman made for Chrome, is after a video is played, prompt the user for a rating, and a reason for the rating. Joe had a taxonomy of human values for this, but it could also be a freeform tag based system.

Then when you go to YouTube next time, you say that the reason you're at YouTube is to "increase my knowledge of machine learning." Or maybe it's Friday evening and you just want to "make me laugh."

Most people probably won't pick "make me outraged or scared.", but that does give good engagement metrics...

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Re:Ask HN: Why is making a good recommendation system for Yo... by swyx on Wednesday December 23, 2020 @01:10PM (#25520298)

if anyone here works at YouTube i'd actually genuinely like to know if it is an explicit goal to make people "watch the maximum amount of YouTube" (or something spiritually similar). It sounds unfathomably wrong to me to maximize for this, on this side of the fence. you couldn't pay me enough to work on something like that.

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Re:Ask HN: Why is making a good recommendation system for Yo... by em500 on Wednesday December 23, 2020 @01:24PM (#25520448)

I don't work at YouTube, but I'd like to play advocate for the devil and see how far I'll get.

Premises:

1. YouTube's primary function is entertainment. Many people also derive educational and informational value from it, but that's incidental. Wikipedia and Google News probably serve that purpose better.

2. The most straightforward way to measure how well YouTube serves as an entertainment channel is viewer minutes. There are drawbacks to measuring per-session or per-view minutes (short term outrage spikes can backfire later), so it's better to maximize life-time viewer minutes. These can't be measured directly, but need to be modeled/predicted. But it's a refinement of viewer-minutes, not a fundamentally different metric.

Contention:

Maximizing viewer lifetime minutes is the best practical way for YouTube to serve it's primary function.

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Re:Ask HN: Why is making a good recommendation system for Yo... by entropicdrifter on Wednesday December 23, 2020 @01:22PM (#25520415)

The non-premium user is the product, on Youtube. They're selling your eyeballs to advertisers unless you're a Youtube Premium subscriber, but even then they use the same algos because they want to maximize engagement. It's the same tired BS as Facebook.

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Re:Ask HN: Why is making a good recommendation system for Yo... by phaemon on Wednesday December 23, 2020 @02:09PM (#25520929)

I don't work for YouTube.

But what if I told you that 30% of users who stop watching YouTube go on to use a different media service, even though they could have watched exactly the same content on YouTube. Would you feel comfortable informing these people that they could watch on your site?

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Re:Ask HN: Why is making a good recommendation system for Yo... by swyx on Wednesday December 23, 2020 @02:25PM (#25521109)

given these terms then yes, sure. i dont feel its a realistic scenario though.

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Re:Ask HN: Why is making a good recommendation system for Yo... by phaemon on Wednesday December 23, 2020 @03:48PM (#25522040)

That's the sort of scenario that would be presented to you. If it happened to engage some people that would otherwise have spent some time with their family, that would not be mentioned. I didn't have to argue very hard to get you to agree to this job.

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