I never understood why Youtube didn't have uploaders select various categories for videos. It would do a number of things:
* allow them to demonetize / ban / block videos for abuse of categorization
* train machine learning on the various categories
It's a lot more socially palatable for Youtube to say "Hey guys, we HAVE a blood and violence category, but you didn't use it for this video. So we'll punish you for that."
Instead, we get programming videos getting demonetized / blocked for god only knows what reason. That makes people made, and is bad press.
YouTube does actually have video categories that the uploader selects, although historically it has led to people mis-categorizing their videos on purpose.
For example, before gaming was a category that was embraced by YouTube, many popular gaming creators would categorize their videos under Comedy instead of Gaming, because the Gaming category did not have a spot on the front page. This also led to a fights between gaming YouTubers over mis-labelling under lesser used categories just to get the top spot and end up on the front page.
As far as I can tell the categories are as follows: Autos and Vehicles, Comedy, Education, Film & Animation, Gaming, Howto & Style, Music, News & Politics, Nonprofits & Activism, People & Blogs, Pets & Animals, Science & Technology, Sports, Travel & Events.
Other commenters speculate that there is a technical reason why YouTube doesn't allow content producers to choose their monetization categories but I bet it's more likely to be a business reason. I'm sure it would be technically challenging and possibly for not much reward (for Google), however, I bet it's even harder to sell advertisers on ad packages that include Google ads when any producer can opt out of any group of ads. It would make it much harder to tell advertisers how many eyes their ads would actually make it in front of.
That seems like a reasonable idea to me but I think part of the answer is that a mind boggling amount of videos are uploaded to Youtube every second. Tracking categorization abuse seems straightforward in theory but good luck automating that reliably over millions of videos especially when you know that some very dedicated people will try their best to game the algorithm in their favor.
People will start using the "blood and violence" category exclusively if it means they're less likely to be demonetized, rendering it useless. Or the other way around: if this category means they get fewer views they'll try their best to be always nearly avoid it, except of course it can get very subjective and some people are going to be flagged "blood and violence" even though they argue it's not that violent and channel XYZ did worse and didn't get tagged etc...
When it come to moderating Youtube, and given the ridiculous amount of content hosted there, you shouldn't think "how would I do it" but rather "how would I design an algorithm that would do that". And suddenly it becomes a lot less obvious. You can't teach algorithms common sense (yet).
I think the reason YT avoids this is for fear of monetization loss as fewer things get exposed to wide audiences so there is less "vitality", and YT loses advert potential.
If they cared about users and creators, they'd take a page from Flickr.
this would be an extremely dirty dataset, as there is no incentive to not put your videos in as many categories as possible. if you can only have one, people will still put it in the most popular category a large fraction of the times I'm sure, not the correct one
The implicit goal of most YouTubers is to get views, as that's how they make money. Putting your video in a smaller category/in not the max amount of category reduces your exposure, reducing your potential views. The incentive of having a lesser chance of being flagged feels tiny compared to that
Which they would determine using... an automated algorithm which decides which category a video should be in, and comparing it to the category chosen. At which point...
Well, it's both a challenging production task (which Google is great at) and a learning from streaming data task, which Google also has some experience with e.g. news. The latter is certainly a interesting challenge, but many researchers are already working on it.
They have more data than they do now for machine learning, and a better PR story.
i.e. uploaders can't be mad about the categories, because the categories are chosen by the uploader.
Uploaders can be mad about Youtube double-checking the categories and getting it wrong... which is less likely to happen if they have better data for machine learning.
Ultimately the determination is still made by the machine learning process, so you're describing extra work to provide an interface of dubious value that will be used more to misrepresent video content than to provide useful signals, and it seems that customer support related to this would increase dramatically.
I think Google relies overmuch on questionable ML in most areas, but in this case, the alternatives are either ridiculously expensive, or easily exploitable.
* allow them to demonetize / ban / block videos for abuse of categorization
* train machine learning on the various categories
It's a lot more socially palatable for Youtube to say "Hey guys, we HAVE a blood and violence category, but you didn't use it for this video. So we'll punish you for that."
Instead, we get programming videos getting demonetized / blocked for god only knows what reason. That makes people made, and is bad press.