231–240 of 279 posts
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"When I invited tagging" is such a flex. But creating delicious gives you some credible claims there.
Content tagging in online systems has existed since at least the 1970s, with the earliest example I can think of being MEDLINE https://en.wikipedia.org/wiki/MEDLINE
I am too but I've given up. I've collected a lot data over the years and spent a lot of time trying to organize it so I can find relevant connections. It's just too time consuming. I've decided discerning relationships in unstructured data is where I want to focus.
It's nice to be able to put on "uplifting saxophone" or "dark dramatic piano"
The problem with tags is that they are the first and often only metadata available to represent the complex relationships between elements. So everything goes in it: tags for the semantic (ontology is rabbit hole in itself), tags for relations with other items, and not forgetting the tags project management (priorities, people, milestone,...).
Want to empower your tags, for instance adding hierarchy or dynamic tags? Then every tag will get these features and associated problems. A solution would be to have tags of different "types", each processed differently, and migrate the metadata from a "bag of tags" to "a bag of bags of tags". But then tagging wouldn't be as simple writing a name in a field.
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Right, but it was never meant to specialize in user-directed filtering and discovery to the level you are describing. To your second point, every social context that gets 'cool' eventually gets LCDed into mediocrity (even HN). You have to outrun the noise, as you described in your #gothgothgoth example
>Right, but it was never meant to specialize in user-directed filtering and discovery to the level you are describing. this, and what you said earlier >Isolated hashtags on IG were often not useful for finding specific content. To find what you want you'd need an interface to a page that showed posts across multiple hashtags which they didn't provide. forgive my naivete but I wonder exactly what could possibly have b…
This is kind of like that, call it 'directed spontaneity'. You open the app to see interesting stuff, but you don't know what exactly that might be in advance. The app learns some basic stuff about you using your interactions on content then tries to guess. You either like the stuff the app shows you or you don't.
The hashtag system was very good at filtering content to what you generally like in your feed and the Explore view, but it wasn't set up for you to fully guide your own experience in search of very particular content using individual hashtags.
I'm surprised I haven't seen more discussion of how tags are an entry point into plain-old data architecture. It should be obvious that by the time you're using tags for queries like "start-date: BEFORE 2022-03-01", you've created an inner-platform where you're building a plain-old relational database on top of your tags. Stop what you're doing and elevate "start date" out of tag-land and into a more structured repre…
I can't wait for the author of this thread to discover the AO3 tagging system, which is, frankly, a masterpiece that demonstrates how effective community management can lead to extremely good tagging and categorization, with very little miscategorization. https://www.wired.com/story/archive-of-our-own-fans-better-t... https://archiveofourown.org/faq/tags
https://twitter.com/hillelogram/status/1579942625242931200?s...
Hillel actually mentioned it cursorily in the thread.
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Right, but it was never meant to specialize in user-directed filtering and discovery to the level you are describing. To your second point, every social context that gets 'cool' eventually gets LCDed into mediocrity (even HN). You have to outrun the noise, as you described in your #gothgothgoth example
> Right, but it was never meant to specialize in user-directed filtering and discovery We agree: > Instagram's ontology is designed to not make this possible, because everything about it is meant to facilitate tube-feeding So as the user-directed ontology component of the IG ecosystem, it's trash, and I will die mad about it. > every social context that gets 'cool' eventually gets LCDed into mediocrity (even HN) I wa…
I'm not sure why you think the whole hashtag system was trash because of this one aspect. Most of the evidence I see is contrary to your statements.
To reiterate, the strength of the tagging system is the relationship between the tags you interact with, not any given individual tag. Also, individual tags are not exclusively literal descriptors for their content. They may be, or they may be used like: 'people who like #jenniferlawrence will also like #...'
Anyone have a suggestion for a tagging filesystem that is maintained? Or if not a filesystem, something that at least works? I still feel like this is the best way to organize personal photos and media, and while https://www.tagsistant.net/ is pretty good it hasn't been updated in 6 years and is fairly buggy.
I just gave up and mimicked tags with symlinks and subfolders. ie "foo" is tagged "todo" if there's a symlink to it in "Tags/todo/". It works surprisingly well, since I can manage it with standard shell scripting.
https://twitter.com/mikeybtags/status/1582509479806980096?s=...
I wonder what disadvantages such a tag hierarchy has?
I imagine enforcing the acyclicity is hard/effortful.
Using (inherently hierarchical) folders (with no symlinks for folders) enforces the acyclicity constraint, and avoids diamond issues, so that’s neat.
I adore tagging systems and have worked on them in several different applications and implementations, but there are always pitfalls and trade offs, and it’s possible to bury yourself Nowadays I nearly always store the assigned tags as an integer array column in Postgres, then use the intarray extension to handle the arbitrary boolean expression searches like “((1|2)&(3)&(！5))”. I still have a tags table that stores…
The tradeoff here is that you lose the foreign key constraint, correct? So if you delete a tag, there is no way for the database to automatically remove all references to it. Or is there some way to do this now?
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> For example, posts that contain both #jenniferlawrence and #hoodedeyes would be what you are looking for I mean, not to overwork it, but in this example, this isn't accurate: I just want pictures of Jennifer Lawrence, not the much smaller slice of content where the poster had her particular eye shape in mind. Also, I don't want to only "end up seeing" pictures of Jennifer Lawrence in my main feed, I want to be able…
Right, but it was never meant to specialize in user-directed filtering and discovery to the level you are describing. To your second point, every social context that gets 'cool' eventually gets LCDed into mediocrity (even HN). You have to outrun the noise, as you described in your #gothgothgoth example
The Law of Shitty Clickthroughs by Andrew Chen illustrates and details this very well: https://andrewchen.com/the-law-of-shitty-clickthroughs/