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Comment by kalleboo | Hacker News Reader

It’s fascinating how differently the YouTube algorithm treats people. I've not once seen a Fox or CNN video recommended, I didn't even know they had a presence on YouTube

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Personalization makes it incredibly hard to "watch the watchers," because everyone is getting a slightly different view of what Google is doing. I would like to see a program where users submitted data about their recommendations to researchers so that we could uncover Google's opinions. It would have a lot of financial value to YouTubers and would make it harder for Google to abuse their role as censor.

I could imagine shadow-burning YouTubers without banning them by shrinking their recommendation audience.

Further, it would be good for Google. Every little shift in the weather is going to get blamed on them whether they deserve it or not, now that it's common knowledge that they weild this power in more than zero cases. Google is about to discover why judges write opinions. Administering justice from secret meetings leads to popular dissent more than it leads to justice.

I clear my YouTube search and watch history about once a week. Partly because of privacy, but also because a single binge of, say, metal casting videos does not mean I want them recommend ever again in the future.

They use browser fingerprinting and/or IP addresses as well. Even on a brand new browser session, doing something even slightly related to the previous session brings back its entire recommendation history.

Yeah, the fact that I can clear cookies, open a private browsing window with tracking protection turned on, go to YouTube, and be asked which of my two gmail accounts I want to log in with, is pretty creepy.

> doing something even slightly related to the previous session brings back its entire recommendation history.

Are you sure that it does, and that it's not just a case of "hey we've never seen this person before, but they watched X, let's immediately start with recommendations Y and Z because other people who watched X were engaged with it?"

I used to think that and gave them the benefit of the doubt, but then I realised that some of the videos being recommended had nothing to do with the one currently watched other than the fact I watched similar ones previously.

How does that work at, say, the library, or some other public internet kiosk? Or maybe they're just assuming these are edge cases today, amidst the billions of private browser instances on handhelds?

It probably doesn’t work, considering the library users would be watching totally different & unrelated videos, where as in my case they have years of data of very specific viewing habits centred around a few topics.

Yes you are right they are using browser fingerprinting, but with the right tool they can easily change it. They can use Kameleo software or Multilogin etc. https://kameleo.io/

One thing this opens you up to is the average recommendation, which is biased towards inflammatory or click-bait content.

I do it every week as well and the recommendations start off being seeded from my subscriptions, not from the trending tab.

The problem with this is that it then just suggests the content that hits the front page instead - so for the most part a load of crap. All I'm doing is swapping recommended videos on, say, metal casting, for YouTube's "on-brand" content creators which pump out generic content on a bi-daily basis at 10 minutes in length.

My understanding is the the only part of YouTube that is not personalized (except by region) is the "trending" tab.

It means it is the most representative of what would be a common YouTube experience.

It thinks I’m addicted to opiates because of the suboxone ads it presents, only because sometimes I listen to 90’s techno, rave music.

Not Google, but Twitter thinks I’m a 45 old married male with 3 kids

I’m 39, divorced, and have 2 kids

It’s almost as if the big data sales pitch is an epic joke like nuclear powered everything being pitched in the 50s

Twitter is a mess in general. No wonder they struggle to monetize.

What? That is an incredibly accurate profile derived from random tweets / follows, and certainly accurate enough to serve you ads.

Fair point. Except I don’t post, follow feeds only, put nothing about my personal life in my profile, and they asked for my birthday.

So my point was aimed more at advertisers buying on Twitter: they filled in the blanks and got them all wrong. And the one they had the data for they got wrong.

That and I’m not a internet consumer really. Twitter can see I’ve blocked over 1,000 accounts that promoted tweets. Is that statistic being shared with advertisers?

Likely not. Advertisers believe so who cares.

It’s so ephemeral as to be useless.

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