> TikTok takes the content you have seen and implicitly shown that you like, and shows you diverse content that has some of the features you seemed to enjoy, while it learns from that.
In my case the recommendations had nothing to do with what I had liked or shown interest in. It was equivalent to visiting Reddit’s /r/popular, which might appeal to most people, but from an algorithmic perspective then there’s nothing impressive about it. Like I also mentioned in another comment, I think there’s nothing wrong with this approach, I just don’t understand how people can be impressed by it from a technical point of view.
> If you are looking to fetishise young Asian women, then maybe you are on the wrong type of website (and: maybe you shouldn't do this).
I was just trying to conduct the most simple experiment imaginable to see whether it was actually capable of detecting what I showed interest in and do so in a way that I could easily verify the results. What I was looking for in the experiment represent perhaps 20% of the userbase, yet it was still incapable of displaying a single post that matched what I was trying to achieve (because the feed just show what they believe is interesting in your area). I could also have tried to achieve something more complex, like train TikTok to show skateboarding videos (which might represent less than 0.001% of their videos), but I figured I’d try with the easiest thing imaginable first (which it failed at).
And I fail to see why there’s anything wrong with being interested in watching content of people within a certain age group, or gender, or nationality..
If I were a TikTok user then I’d surely hope that they were able to recommend my videos to people that were interested in the kind of content I posted (because that would open up a lot of possibilities, like meeting people with similar interests, selling products, etc.)