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Really cool project, going to play around with it, since I wanted to experiment with alternative algorithms for these kind of platforms for a while, but didn't found time to get started. My biggest gripe with YouTube recommendations, or any service of that kind (Spotify, Amazon, etc.), is that they don't understand what aspects of the content I value. So it is a huge hit and miss. Sometimes it works, because I guess I just happen to value the same things that the majority of people do, other times, I might watch an hour long very in-depth video about a topic, then YouTube for a week or so tries to get me to watch 5 minute, rather shallow introduction videos that are way more popular. There is nothing wrong with those videos per se, they are often really well made, but it is not what I'm looking for. Other times it picks stuff up from the long tail that seemingly gets into a feedback loop, suddenly reaching millions of view, with practically zero relevance to me. Then there are some personal tastes of mine, e.g. that I can't stand the, I guess I'd call it the "Youtube Voice" where creators go completely over the top instead of talking like a normal person. I wonder what metric could be used as a proxy to get better recommendations? Or if a better approach would be, to just build a better custom search so I can tweak it to what I'm looking for at this moment in time. |