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This reminds me of an episode of 99% Invisible [0] that I listened to. That episode also covered a bit about the history of indexes (which is relevant to the history of alphabetical sorting), including how scholars feared and resisted the adoption of indexes. It was super fascinating and I highly recommend giving it a listen if you found this article interesting!

[0] https://99percentinvisible.org/episode/alphabetical-order/

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Imagine if we could sort Google search results alphabetically. Imagine if we could sort Facebook "News Feeds" by any criteria. How would this affect advertising.

There is a book some folks mention written about alphabetical order. There was also a book written some years prior about the telephone book. Google has obliterated alphabetical business listings.

> Imagine if we could sort Google search results alphabetically. Imagine if we could sort Facebook "News Feeds" by any criteria. How would this affect advertising.

AAAAAASEO.com will be the first result for every search.

If the sorting is by domain name, I usually find 0 comes first. Something like 000000AAAAAASEO.com. There is now a .aaa gTLD. Perhaps they would cash in. Thus the first result might be 000000AAAAAASE0.aaa

Sorting by business name might make more sense. Naming a business tends to rely on trademark law, which IMO is a better system for resolving name disputes than the ICANN domain name system.

Thanks for that. Now I have 530 episodes in my podcast queue :)

On a side note, I've always wish there was an API that could recommend media content.

Like you could just plug it into any playlist of songs, movies, or books, have it do some algorithmic analysis, and spit out what you would probably find fascinating.

You've basically described recommendation engines generally and they tend to deliver mediocre to awful results for a bunch of different reasons. I remember hearing talks on the topic over a decade ago and things haven't really gotten much better--and my sense is that most people have given up on actually creating a good engine.

I’ve found much better results using your lists to find people with some overlap, and then looking at what they have.

Which is basically what HN is.

Do recommendation algorithms not take this into account already? Perhaps privacy policies make it harder to automate this effectively.

The famous ones may, but it ends up taking into account "what do we want you to see/listen/look at" much more into account.

The original Netflix prize also, it turned out, wasn't really implemented for a number of reasons. But one of them was apparently that Netflix doesn't necessarily want to give you the best recommendations; it wants you to keep your subscription. There's certainly some overlap between those objectives but they're not the same thing.

They're also incentivized to show you things that cost them "nothing" or "less" than others things - and if they KNOW the things you'd like to watch it's better for them to string those out so you keep subscribed.

The perfect Netflix customer is one always on the cusp of cancelling from lack of use but never actually does ...

In addition to the cost angle, they're also incentivized to push you towards exclusives. Things you can watch on other services (assuming you subscribe and know they're there) are much less of a hook to keep you on Netflix.

I have played ~5 seconds of one random episode from the front page on my Netflix profile since i subscribed around 2016. This was just to verify that it worked.

It still chuckles me up when they send me an e-mail once in a while, about what I might like based my past viewing preferences.

Note: My GF, has a profile that she uses sometimes, but mine haven't been used since the account was created.

It depends what the overlap is of course. Something like music probably has a big age component in what people like for example.

But, yes, in general friends with at least reasonably similar preferences to myself are almost certainly a better source of recommendations for video, music, and books than a recommendation engine.

I remember when Pandora was attempting to compute the "DNA" of a song (assorted classifications like key, tempo, style) and recommend music based on that. You could then get a "station" based on a single song, and fine-tune it by adding more or disliking songs as they came up.

The end result was underwhelming- it never really captured the characteristics that I actually liked about particular songs, and ended up being crappy or so narrowly tuned that it lacked enough variety to be interesting.

The concept is still around, but with less scientific sounding fluff and, I think, more relaxed parameters for recommendations.

Did Pandora change at some point?

The last time I used it, I don't recall seeing the "DNA" nonsense, or being able to get a list of characteristics that they used to build a station around... It's possible that the interface simply changed and I didn't look hard enough for it though.

It's still using the same type of algorithm

Pandora is based off of the "Music Genome Project" which was a massive effort that took tons of music efforts to make happen. Experts literally sat down and deconstructed individual songs by hand and gave them tags.

It's truly a historic achievement and it's almost sad how the massive effort mainly resulted in a private database that's primarily used for a failed Spotify competitor

I am 100% with you there. The things that could be done to advance the creation, understanding and appreciation of music from that work is staggering. It's sad that it's stuck in amber.

>You could then get a "station" based on a single song

Apple Genius did something similar and it mostly worked not badly because it was drawing from songs in your collection already.

You're more likely to like songs in specific genres and time periods and songs that are popular generally. Once you get beyond that, it gets harder. And the situation is probably even harder with video unless you basically watch superhero films.

I worked through whatever the length of the queue was in 2017 over the course of a summer and a long driving commute :)

It's a really, really great show. You won't regret it.

There are still modern authors who buy into this kind of argument. E.g. the late John Taylor Gatto, who refused to use footnotes because he thought they made readers dumb. I forget whether or not his books have indices.

Sorry to hijack you but I can’t help my curiosity.

  Index: 1) a pointer 2) a structured collection of pointers
  Indices: two or more pointers
  Indexes: two or more structured collections of pointers

(Where “pointer” is used in a slightly generalized sense, like “reference”)

Yay or nay, pedants of HN?

"To index" means to point, as with your index finger. An index, such as at the end of a book, serves to point into the main body of the work. In this context, I think of an index like a mass noun; the whole thing serves the purpose of pointing, so one does not count the individual entries to quantify the whole. This is the same sense as in database indices, I think.

I don't really make a distinction between "indices" and "indexes"; it seems more a matter of how integrated "index" is into English, since "indices" would be (I believe) the Latin pluralization, while "indexes" uses the more typical English plural scheme. They index (ha) the same semantic meaning in my mind.

(We have the same issue with "appendix" and "appendixes" vs "appendices". It's telling that neither spelling bothers iOS as I type this.)

Then you have octopus with many plural forms: octopuses, octopi, octopodes (oct-oh-pohds, oct-o-po-dees), octopen, octopees, octopa, ...

As soon as I saw this post I thought it that podcast. It was quite interesting how we take the alphabet as so fundamental. (And with a surname beginning with "V" I was always frustrated at school at being down the back of the line unless an enlightened teacher occasionally mixed it up)

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