I can think of many videos like this, that pop up in a feed after many years and you’ll see the comments like “see y’all again in a year when the algorithm brings this back” or “I always click when this video is recommended”.
I have several friends who’ll rewatch whole shows again and again for a similar reason. There’s the comfort of something familiar.
So I guess I don’t mind when youtube does this
Here is an old, deleted, reddit thread about people who re-watch the same Youtube video over and over: https://www.reddit.com/r/TooAfraidToAsk/comments/h7fqv9/is_i...
1. Music, which often lends towards repeat content
2. Children as a demographic, which any parent will tell you will watch the exact same movie/show/video on repeat ad nauseam.
Because of these, it's likely that YouTube has found that repeats (in general) drive more engagement.
i think people do like watching the same video more than once sometimes though.
But coming back to your question.
This question reminds me of a complaint that I heard from multiple people about Amazon: why is Amazon recommending me a product I just bought? Or a less generous manifestation of this sentiment "duh, Amazon is so stupid, it recommend something I bought give minutes ago".
In reality, people don't realize how often they buy the same and similar stuff again and again. You bought a usb hub for home, you like it, so you but it for the office. If you didn't like it, you may buy three different usb hubs to make sure you find a good one. You like a book, so you but the same for your sister as a gift. Bought some socks, you enjoy using them, so you buy another 10 so that you don't need to worry about socks for the next two years. You realize you love funny socks, so you keep buying more socks.
The same happens with videos. I don't mind watching a video about streams by Venkat Subramaniam every now and then. A conference talk about regex is recommended to me again?? Hmm, actually, I might watch it again because I don't remember half of it and I remember she prepared a great talk.
Then you check new for you and it’s weirdly just like normal fresh browser yt recs, not my algorithm.
When I'm listening to 80s rock, it gives me a bunch of other 80s rock, notably including things I've enjoyed listening to before so I can just yoink that right into my playlist. Also throws in some 2000s dubstep and some 60's country that I like and a couple of things that I've never heard before in case I've started out on 80s rock but just am not feeling it tonight.
When I'm watching thought-provoking mini-documentaries, it gives me more by the same creator along with some random related stuff. Some of that is stuff I've watched before but might want to re-watch or share with someone. Or to compare the thoughts of this guy vs that guy.
Your usage pattern might be different. But for many of us, it works quite well. I would assume they're optimizing for the most common use cases. And yes, I liked that video, I do want to see it again.
I think that what he says pretty much applies to almost everything that seems sophisticated to us such as health tech, privacy tech, fin tech, anti-terrorism tech and of course user behavior prediction tech. A lot of people are convinced that what these companies do is highly sophisticated and very difficult to achieve in terms of algorithmics. Most of the things that look sophisticated are just mediocre at most, with a handful of companies just having successfully delivered on a handful of problems and pretending to have solved many others.
One of the reasons I suspect i they're failing at so many things is that these companies have focused extensively on hiring the brightest minds to solve the most difficult problems they had to solve 10-15 years ago.
During all this time they failed at solving simple problems that do not require the brightest minds in the world but just people who actually can discuss with other people and solve simple problems with their technologies.
You're perfectly legitimate in hoping that YouTube would have solved these problems but no, they haven't, they're actually quite weak at solving many simple things and it is crucial that the large audience doesn't realize that.
I do however watch “Picard make it so (let it snow)” every year. Some videos I’ll watch more than once throughout the year.
On the other hand it’s rare I’ll watch a Numberphile or Tom Scott video more than once, and when I do I deliberately seek it out
Charge for ads, get longer engagement, drop the nasty rabbit holes as other subscription models are more informative, etc. Encourage better content to boot.
There are a LOT of ways to organize their content model, their current model pains me as a consumer, an economist, and with due respect would be indistinguishable from a catastrophe of ego tripping product owners.
Today, when I found this thread, I started looking for past HN threads discussing this topic. I came across a 2019 thread (https://news.ycombinator.com/item?id=18999326) where a similar discussion was held. In that post, a user mentioned the following:
> "Read the YouTube recommendation paper (https://ai.google/research/pubs/pub45530) and it will become clear why it recommends a ton of high-engagement, clickbait-y content based on a minimal set of recent watches."
I skimmed through the paper, and they have some interesting stuff in there! Maybe I should read it more carefully later. Here's some I found:
> We consistently observe that users prefer fresh content, though not at the expense of relevance. In addition to the first-order effect of simply recommending new videos that users want to watch, there is a critical secondary phenomenon of bootstrapping and propagating viral content.
> Consider as an example a case in which the user has just issued a search query for “taylor swift”. Since our problem is posed as predicting the next watched video, a classifier given this information will predict that the most likely videos to be watched are those which appear on the corresponding search results page for “taylor swift”. Unsurpisingly, reproducing the user’s last search page as homepage recommendations performs very poorly.
This is probably the most interesting one!
> We observe that the most important signals are those that describe a user’s previous interaction with the item itself and other similar items ... As an example, consider the user’s past history with the channel that uploaded the video being scored - how many videos has the user watched from this channel? When was the last time the user watched a video on this topic? These continuous features describing past user actions on related items are particularly powerful because they generalize well across disparate items...
For example, Hulu showed that recommending shows similar to "recently watched" rather than "watched in the past" increases CTR by 188%. In particular see the graph at the end which compares "recently watched" recommendations to other types: https://web.archive.org/web/20120130230618/http://tech.hulu....
I wish they would improve the algorithm to distinguish between things I want to replay like music versus things I want to see once like a documentary.
Nothing against Joe Rogan. It's just weird how I get so many video recommendations for him, even though I've never watched one.
I get the same short suggestions repeatedly but sometimes they're mixed in with very new, low quality stuff with no comments or likes.
My youtube time has gone down precipitously, which is a good thing for me, but not for youtube.
I agree: it makes it seem like there are a couple hundred videos on YouTube, and they keep trying to shove the same ones down my throat.
Obviously the algorithm has no way to know your friend isn't standing right there right now and demanding to be shown something you've already seen but think is cool...
Not interested ->Tell us why ->I've already watched the video
Not interested ->Tell us why ->I've already watched the video
Not interested ->Tell us why ->I've already watched the video
. . . . . . .
I would assume that all the minecraft, sports, and vlogger stuff is what I get because it’s trending, but i also have zero interest in any of that stuff at all.
Because it works. I'm ashamed to admit I rewatch a lot of videos on YouTube.
Scrolling through some of the comments on Jordan Peterson videos I have found that his fanbase does seem to be a little on the fanatical side. (Just to be clear this is not a knock against Jordan Peterson - I actually find him pretty interesting. Nor do I think his fans are uniquely fanatical - lots of YouTubers have fanatical fans. But because he is in the realm of self-help and politics, and he tends to be very opinionated, he does tend to attract some really hardcore fans who I could imagine rewatching his videos from time to time).