Hi! I'm the dev here! I built this on a whim at after seeing someone ask for it on twitter. It was 12:30 at night but I couldn't pass down the opportunity to build it.
The code is very simple, there's no backend at all actually, I believe because wikipedia's api is very permissive and you can just make the requests in the frontend. So you just simply request random articles, get some snippets, and the image attached!
I used Claude and cursor do 90% of the heavy lifting, so I am positive there's plenty of room for optimizations. But right now as it stands, it's quite fun to play with, even without anything very sophisticated.
Wonder what it would take to add a simple algorithm to this. Part of what makes short media apps (dangerously) addictive is that they eventually learn what you like and feed you more of that. An app like this with such an algo could help with the stickiness (and presumably get us away from the other apps at least for a little bit). "Oh this person likes science stuff, let's feed them more, oh they specifically like stuff related to quantum mechanics, let's place a summary paragraph from a related page topic in there."
On one hand I am thinking about what a very basic algorithm would like (maybe even just categories I might do) and maybe how it would make people happy.
On the other hand, I'm not sure exactly the details of wikipedia's api TOS. Also as it stands this website is entirely in the frontend at the moment, and I'm enjoying just scaffolding out what I can with limited a more limited set of tools to speak.
I realize now the suffix "tok" implies a crazy ML algo that is trained every single movement, click, tap, and pause you make, but I don't think I really want that.
For each 10 seconds of reading, increment the tags on the current article as "favoured". Then, poll randomly from those tags for the next recommended article. Add some logarithms of division to prevent the tags from infinite scaling.
The relatedness of articles is already baked in with blue wiki links too. So it shouldn't be too hard to make something that just looks for neighbors.
Now, something that learns that if you like X you might like Y, even if they are disconnected. Is closer to the dystopic ad maximizing algorithm of TikTok et al.
That's what I was thinking this might have already. Maybe this could get insights from the articles linked from the ones you like too? Sort of like https://www.sixdegreesofwikipedia.com/
This would eventually collapse to people reading articles they do not actually like (i.e. get happiness from reading), I think, maybe tragic history facts or something like that?
The truth of social media harm is that it's more about humans than the algorithms themselves. Humans just tend to engage more with negative emotions. Even IRL we tend to look for intrigue and negative interactions, just look at the people who stay with toxic partners even with no financial ties, or even friend groups who turn into dysfunctional gossip fests. The only way to avoid this is by actively fighting against this tendency, and having no algorithm at all in an application helps.
Since its text, especially text with links to other articles, there is no need for tags.
If I had a clue how to do this (sorry, just a neuroscientist), I would probably create "communities" of pages on a network graph and weight the traversal across the graph network based on pages that the person liked (or spend X time on before).
it starts with sourcing - finding a massive set of interesting pages, then going through and giving them tags. planning on adding this to my web discovery app as well: https://moonjump.app/
Awesome. I have a project with a similar tik-tok-esque philosophy for serving all sorts of noncommercial content from the web. The interface is one button and a random page is embedded in an iframe. I use random wikipedia pages as a fallback in case my algorithm returns a dead page.
This is awesome. I've been passively looking for a Stumbleupon replacement, but never stumble upon it. Thank you for posting here. You have given me back a slice of old internet.
I like the idea, but one thing about Wikipedia is that with technical or granular topics it approaches things in a focused way. A specific molecular biology term's page isn't there to explain exactly how it fits into a larger biology topic. It makes random pages difficult to glean information from.
Even wikipedia articles I understand, more on computer topics, fall into the category of "the only people who understand this page are people who ... already understand it / don't need to read this".
Granted sometimes the social media context is kinda opaque, but usually "man fall down it funny" is pretty universal.
Some other commenters have offered the idea of an algorithm to steer the randomness of the articles. I wonder if an algorithm would help with this issue of having random articles be too technical for you even though you are interested in the larger topic.
This, plus an AI generated voice reading a TikTok-creator style catchy summary, plus TikTok's actual algorithm for surfacing content would actually make a decent app I believe.
EDIT: Also the name should be WikTok instead of WikiTok.
I just admire how some people can build simple things. I see so many from simple games to visualizations to many other kinds on HN here. Hopefully someday I will be able to think of something simple and showcase here.
I am a big fun of Wikipedia and sometimes TikTok (a "guilty pleasure"). I would be happy to have an app/web site like this but with
- more smart feed based on your activity/attention (was mentioned in other comments);
- maybe more fancy way to present information (not sure if it is feasible to implement). Currently just a text snippet and image do not seem like super engaging.
Good question: i had that thought for a second. But the I realized that for me, Incan imagine killing time here, but not in the random page. It is an image and a short text which allows to decide fast if it is interesting or not.
I used to take a technical dictionary, and read random articles when bored. So I tried with random wiki, but just didn’t work. I will try this and I can already say, it will work.
It sounds like you’re suggesting the two web pages are identical, just on different domains, but they’re obviously completely different.
A better way to phrase your question would be: "Why would a TikTok-style (infinite scrolling) website for browsing Wikipedia articles appeal to today’s internet users?"
I’ve been thinking recently about how to use the addictive properties of applications like TikTok to the advantage of the user. This is definitely in that direction. Instead of trying to tame the pull of these apps by cold turkey quitting, replacing them with something useful seems to be more effective.
I don’t know how to feel about the visceral reaction that I have to the action of swiping my thumb in a movement that I can trace from where I guess is a team of tendons somewhere parallel to my wrist and the little fat part of my palm I like to refer to as “my drumstick”, from the bottom of my phone’s screen until the tip of my thumb is just at my general line of sight, all of this in one natural motion. No sooner is this action complete am I met when an entire block of information above my thumb, square in my line of sight.
In one stroke the location of a place, the type of place it is, its size, its distance from somewhere else, its history, read more, or swipe again. And another block. And another. And there’s something about this process that is visually disruptive and kinetically unsettling.
Interesting! I tend to use right hand index finger to swipe up so didn’t have that issue. Just tried it with left hand thumb and I kinda see what you mean.
This is very nice, I adore the simplicity. Sometimes the summary gets cut off which is a bit frustrating,I think you should be able to finish reading the summary without click the read more link, but other than that, bravo.
[+] [-] aizk|1 year ago|reply
The code is very simple, there's no backend at all actually, I believe because wikipedia's api is very permissive and you can just make the requests in the frontend. So you just simply request random articles, get some snippets, and the image attached!
I used Claude and cursor do 90% of the heavy lifting, so I am positive there's plenty of room for optimizations. But right now as it stands, it's quite fun to play with, even without anything very sophisticated.
Here is the source code. https://github.com/IsaacGemal/wikitok
[+] [-] xhrpost|1 year ago|reply
[+] [-] aizk|1 year ago|reply
On the other hand, I'm not sure exactly the details of wikipedia's api TOS. Also as it stands this website is entirely in the frontend at the moment, and I'm enjoying just scaffolding out what I can with limited a more limited set of tools to speak.
I realize now the suffix "tok" implies a crazy ML algo that is trained every single movement, click, tap, and pause you make, but I don't think I really want that.
[+] [-] aDyslecticCrow|1 year ago|reply
[+] [-] TZubiri|1 year ago|reply
Now, something that learns that if you like X you might like Y, even if they are disconnected. Is closer to the dystopic ad maximizing algorithm of TikTok et al.
[+] [-] easterncalculus|1 year ago|reply
[+] [-] mvieira38|1 year ago|reply
[+] [-] marci|1 year ago|reply
Rabbit-holing as a service
[+] [-] tbossanova|1 year ago|reply
[+] [-] hummuscience|1 year ago|reply
If I had a clue how to do this (sorry, just a neuroscientist), I would probably create "communities" of pages on a network graph and weight the traversal across the graph network based on pages that the person liked (or spend X time on before).
[+] [-] ya1sec|1 year ago|reply
[+] [-] ya1sec|1 year ago|reply
I call it moonjump: https://moonjump.app/
[+] [-] aizk|1 year ago|reply
[+] [-] sgt|1 year ago|reply
[+] [-] therealfiona|1 year ago|reply
[+] [-] Tijdreiziger|1 year ago|reply
[+] [-] extraduder_ire|1 year ago|reply
[+] [-] duxup|1 year ago|reply
Even wikipedia articles I understand, more on computer topics, fall into the category of "the only people who understand this page are people who ... already understand it / don't need to read this".
Granted sometimes the social media context is kinda opaque, but usually "man fall down it funny" is pretty universal.
[+] [-] myself248|1 year ago|reply
[+] [-] layman51|1 year ago|reply
[+] [-] TZubiri|1 year ago|reply
That is provably false
[+] [-] Matthyze|1 year ago|reply
[+] [-] joshuahedlund|1 year ago|reply
[+] [-] doctoboggan|1 year ago|reply
EDIT: Also the name should be WikTok instead of WikiTok.
[+] [-] mikedelfino|1 year ago|reply
[+] [-] CaptainFever|1 year ago|reply
Like this: https://pdftobrainrot.org/
[+] [-] srameshc|1 year ago|reply
[+] [-] zavg|1 year ago|reply
I am a big fun of Wikipedia and sometimes TikTok (a "guilty pleasure"). I would be happy to have an app/web site like this but with
- more smart feed based on your activity/attention (was mentioned in other comments);
- maybe more fancy way to present information (not sure if it is feasible to implement). Currently just a text snippet and image do not seem like super engaging.
[+] [-] arrowsmith|1 year ago|reply
[+] [-] f1shy|1 year ago|reply
I used to take a technical dictionary, and read random articles when bored. So I tried with random wiki, but just didn’t work. I will try this and I can already say, it will work.
[+] [-] j3s|1 year ago|reply
[+] [-] guessmyname|1 year ago|reply
It sounds like you’re suggesting the two web pages are identical, just on different domains, but they’re obviously completely different.
A better way to phrase your question would be: "Why would a TikTok-style (infinite scrolling) website for browsing Wikipedia articles appeal to today’s internet users?"
[+] [-] AzariaK|1 year ago|reply
I wanted to show a similar site I made a few years ago. Might update it now:
https://wikisurfer.pages.dev/
[+] [-] dustypotato|1 year ago|reply
[+] [-] lucaslazarus|1 year ago|reply
[+] [-] hao1300|1 year ago|reply
[+] [-] whiteborb|1 year ago|reply
[+] [-] unknown|1 year ago|reply
[deleted]
[+] [-] jona777than|1 year ago|reply
[+] [-] rpastuszak|1 year ago|reply
[+] [-] tolerance|1 year ago|reply
In one stroke the location of a place, the type of place it is, its size, its distance from somewhere else, its history, read more, or swipe again. And another block. And another. And there’s something about this process that is visually disruptive and kinetically unsettling.
[+] [-] tbossanova|1 year ago|reply
[+] [-] sirobg|1 year ago|reply
https://news.ycombinator.com/item?id=42946932
[+] [-] russian_bot|1 year ago|reply
[+] [-] coffeecantcode|1 year ago|reply