YouTube’s Rabbit Hole of Radicalization [pdf]

> It should be noted that this research was likely published with a specific agenda in mind:

Just like the previous "study" which claimed everybody not part of the corporate media were alt-right.

These types of "research" are funded and run solely for an agenda. Primarily to push social media platforms to direct traffic to corporate media.

Also, radicalized is such an interesting word. If the saudis ran the exact same study with their definition of "radicals", I wonder how that would turn out? What if the chinese or the russians? Are their radicals the same as ours? Also, are the liberal elites' definition of radical the same as conservatives or the general population at large?

At the end of the day, it's all about "authorative" sources - an orwellian and creepy word if there ever was one.

This quote raises questions: "The scraped data, as well as the YouTube API, provides usa view of the recommendations presented to an anonymous account. In other words, the account has not ”watched” any videos, retaining the neutral baseline recommendations, described in further detail by YouTube in their recent paper that explains the inner workings of the recommendation algorithm[38]. One should note that the recommendations list provided to a user who has an account and who is logged into YouTube might differ from the list presented to this anonymous account."

Many discussions of radicalization talk about recommendations coming after someone has watched a number of videos.

This situation is that after N videos, the algorithm starts to see a pattern, a niche, that the user fits into and then recommends more niche content. Once the user watches the niche content, just more niche content is recommended, or that-niche and mainstream content is recommended and the mainstream content is boring.

In a sense, I don't see how a blind recommendation system could escape this situation. It seems more an inherent problem of blind recommendation systems.

What could be a better approach?

* Better education in the US and the world so people have BS detectors?

* Instead of unlabeled recommendations, the algorithm categorizes what you're seen, categorizes what it's recommending and let's the user say what category they want and remove or add categories for recommendation.

* Have more ordinary search tool and a better categorization system (Youtube is a horrible black-box now, search is terrible, recommendations is terrible, I get videos from other sites mostly).

I mean, of all the different libertarian philosophies, most of them are radical, in so much as they all seek to distance the individual from systems of government and social institutions. Since those things are what most people use day to day, and in the US only one of the two political parties leans that way, it does put you in a minority camp whose views can be felt as a sort of existential threat. (And honestly, politics and religion should both be kept out of most conversations)

I don't follow your logic. Yes, CNN and TYT are very different. This only means they can be tagged differently, but it doesn't mean they cannot be tagged under same category.

For example, The Selfish Gene and Advanced Algebra are two very different books, but they can be both categorized as nonfiction.

Maybe you are right with the conclusion, i.e. CNN or TYT should not be both categorized as “Partisan Left,” but you need a better reason.

> with slant towards left-leaning or politically neutral channels

So ... YouTube is actually politically biased? This would be an interesting study to continue. You would need to normalise for view counts etc. since I suspect there is a bias just in terms of numbers. The biggest channels are more progressive, left leaning, so YouTube could appear left-biased simply by recommending most-viewed videos.