Timing The Speed Of An Algorithm
So, as I wrote on Monday, I’ve started actively using Twitter’s “For You” feed, which is the app’s newest version of an algorithmic timeline. My chronological feed feels extremely dead since Musk’s takeover and I was curious what the other tab had to offer, aside from migraines (which it’s still giving me).
My initial thought was that it was just full of freebooted TikTok videos and pictures of Margot Robbie’s dress. But my take has become a bit more nuanced over the last few days. Twitter has recommended me old clips of old hardcore bands playing shows, this one guy who writes really esoteric takes about menswear, very unwell product managers from San Francisco, and exposed me to violent hatred — and then the subsequent backlash to that hatred — of too many random TikTok personalties to count. People sure have a lot of thoughts about this woman who went on dates in Greenpoint!
But Twitter is about speed and relevancy. If it wasn’t fast and it wasn’t topical it would just be Instagram. So exactly how does Twitter’s algorithm compare to a well-curated timeline when it comes to seeing big viral discussions? Well, I tried to figure it out. And according to my little experiment, Twitter’s “For You” feed is a few hours faster than if you were relying on the site’s chronological feed, but almost 12 hours slower than other sites like Reddit. Here’s how I conducted my experiment.
Across the last few days, if I came across a popular tweet in the “For You” feed, I would bookmark it and write down roughly when I saw it in the course of my day. Then I would note when I saw the same tweet via Tweetdeck, which is the app I have open all day on my computer, which delivers tweets chronologically. For instance, on Monday morning, I saw this tweet about the Street Fighter movie. And didn’t see it on my chronological feed until around lunch time on Tuesday.
Similarly, I saw this tweet about Disney World and walkable cities on Tuesday morning. And I didn’t stumble across it again organically until it popped up in my Activity tab on Tweetdeck until late Tuesday afternoon.
Not the most scientific of experiments, but this delay seems to hold true for a lot of content I’m seeing right now on the “For You” page. I saw this “no worries” tweet last night on the “For You” page and just saw it again this morning on Tweetdeck while writing this piece. So if you’re someone who cares about the macro conversation on Twitter, which I guess would be content marketers, pop music stan armies, and underpaid interns at digital media companies, the “For You” page is delivering that content faster. But what about using the “For You” page to follow the general macro conversation of the internet as a whole? Well, it seems to be pretty slow actually.
Twitter, Instagram, Reddit, Pinterest, Tumblr, message boards like Hacker News or 4chan, YouTube, TikTok, Mastodon, and, yes, even still Facebook, are all in conversation with each other. Despite many attempts from the companies that own these platforms to tweak their content to specifically fit inside their walled gardens, most websites in any given country are all sort of talking about the same stuff every day, which is usually a mix of random news stories, memes, and general internet discourse. But the speed at which they talk these things is different. Twitter has, for many years, been the most influential internet community because its users tend to kick off these macro conversations. While Facebook’s impact on the greater internet began shrinking around 2013, when its algorithm started prioritizing slower, more mass appeal content, which quickly degraded into boomer bait.
Which makes the life cycle this week around this guy’s fried tomato TikTok video all the more interesting.
This is Bayashi, he’s a food creator from Japan. He has 40 million TikTok followers and Reddit absolutely hates him. He’s a regular fixture on r/StupidFood, a subreddit with just under a million subscribers, which loves being angry about his content. I almost never use r/all, Reddit’s main feed, but I do follow r/StupidFood, which is where I saw one of his newest videos. He scoops out the inside of a tomato, fills it with cheese slices, wraps it in bacon, and deep fries it. Not his worst. The Reddit thread about Bayashi’s video was posted on Monday morning, which is around the time I first saw it and shortly after it was first uploaded to TikTok.
Bayashi shared the video himself on his own Twitter account, but it didn’t get a lot of attention until it went sort of viral when it was shared separately by a Twitter account called @fuckedupfoods, which posted an edit of it on Monday night. And I didn’t personally see the video via the “For You” tab until Tuesday mid-day. That’s a pretty big lag.
I’m someone who spends most of my day looking at the internet. So I’m a bit more sensitive to the timing of this stuff than most. But I do think Twitter users will begin to feel this algorithmic lag. Though, I don’t think Twitter users will mind. The “For You” feed is giving them more of what they want and it’s likely to hold them there. And as long as TikTok doesn’t introduce a timeline for text-only posts and links, Twitter will also likely remain in a parasitic relationship with the short-form video app, essentially functioning as its chatroom.
What Elon Musk has done is morph Twitter into Reddit, with gimmick accounts replacing the role of subreddits. The question is whether that will help long-term growth and, more importantly, is it enough to bring back advertisers.
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A Devastating Take
Are Flash Mobs Back?
I’ve seen a lot of panicked New Yorkers sharing this subway dance video worried that it may mean that flash mobs are coming back. First, I wanted to revisit two earlier predictions of mine from 2021 to see if this is in line with what I was thinking about at the time.
In October 2021, I wrote that bizarre TikTok trends like the West 4th Street Puncher panic at the time might “morph into very violent panics, but in the short-term, I think I’m more scared that we’re going to end up with flash mobs again.” OK, so that didn’t happen (yet), which I think is good. And then in November 2021 at the Web Summit, I wrote that “our lives will become an endless and chaotic montage of viral flash mobs and micro-trends, while we’re surveilled by our wearables and screens and projectors. But our robot butlers will be very smart.” A little more on the money perhaps if you replace “robot butlers” with A.I.
Anyways, I thought Ludwig Hurtado, an editor for The Nation, had the best take on the video above, tweeting, “I’ve said it before and I’ll say it again. The return of flash mobs is perhaps the single greatest indicator of a recession.”
A Neural Radiance Field Was Used In A Commercial For The First Time
Of all the A.I. tools out there, I think neural radiance fields, or NeRF, are the most exciting. The company leading the NeRF space right now is Luma AI and the way their app works is you record footage with your own camera, feed it into their A.I., and then the A.I. uses that footage to build a 3D model or takes your camera’s movement and integrates it into another 3D model. Unlike a lot of other A.I. out there, this feels fairly ethical, at least in theory, because most of the assets are coming from you.
You can click through on the tweet above to learn more about how the ad was created.
Discord Bought Gas
Fresh off a fairly lukewarm moral panic last year, Gas, the app that only lets you compliment other users, was purchased by Discord. The app has over a million daily active users per The Verge and will continue on as an app separate from Discord.
Honestly, this is a weird acquisition. I suppose it makes sense that Discord, the main public chat app of Gen Z, would buy Gas, an app that has captured the attention of users who are even younger, but like BeReal, I’m a little foggy on what you do exactly to further grow and develop an app like Gas. So many buzzy Gen Z apps just feel like novelties without any sense of how you could evolve them or turn them into real businesses. Though, I can’t tell if that’s their fault or if it’s because the social networks of the last decade that did become real businesses all just turned into bloated online portals.
The Freshman Dorm Room Theory Of Social Media
There’s an old rule about the internet that has stayed pretty true over the years. It’s called “Eternal September,” and I cite it pretty regularly. Essentially, increased mass adoption of the internet makes it harder to retain a coherent cultural memory. Every time a community gets too big, people start reposting stuff and breaking rules and causing general chaos.
But I think there’s another dimension to this that happens every few years specifically on social media platforms which I’ll call the freshman dorm room effect. Basically, viral content just sort of tends to devolve into weird icebreakers or dumb games a R.A. in your dorm would organize for incoming freshman during your first weeks away at college.
This is technically always happening, but I think it definitely can ebb and flow in cycles. This partially explains identity quizzes being a big thing for approximately four years and then blipped out of existence. I think it also tends to line up with the launch of new social networks. Everything old gets reinvented on new platforms like, say, TikTok, or recirculated by an algorithm like, say, Twitter. Which is how you get a fresh wave of users making relatable content about things like “going to a restaurant alone,” like in the tweet above, which is really just the 2023 Twitter variant of a 2013 Facebook list about things only introverts do.
But I also think this is sort of a natural consequence of the internet having no one at the top really organizing content. Plus, there are teenagers becoming adults for the first time every day on the internet. But this cycle is also a really easy way to build up a lot of followers. And just to further prove my point: Last month, a guy got 30 million views on TikTok for doing the infinite Kit Kat trick.
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“OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic”
P.S. here’s a good text message.
***Any typos in this email are on purpose actually***
That linked article about the Kenyan workers for ChatGPT reminded me of an old job my wife had. She worked for a marketing company that used a deep learning AI. I can't remember the exact technology, but I think it was meant to categorise user comments / reviews. However, as it never worked properly, my wife was hired as part of a team that did the work manually. She was overworked and eventually let go (thank god she's out of there). I'm pretty sure she was resented by her bosses because her presence was a reminder that their deep learning platform was essentially a crock of shit. I'm now convinced that behind each sector of 'automation' there's a small army of workers picking up the slack for the failed promises of the system, and they're hated for it.
Maybe the wrong place for a request, but lately I've been wishing you'd indicate if a Stray Link goes to Twitter because I'd like to avoid clicking anything that +1s their counters. I can tell the others from context--it's just the line links at the bottom that trick me.