Threads’ chaotic “For You” feed quantified
How old are the posts Threads are recommending to its users?
Since Twitter's rapid unscheduled disassembly following Elon Musk's purchase of the platform, hundreds of millions of users have turned to Meta’s Threads as a potential replacement for the newsy town square experience, minus the hate speech and crypto scams.
The year-old platform now has over 200 million users and has been rapidly adding features to achieve golden age Twitter product parity. While users have been praising the improved quality of discourse, and a seemingly functional content moderation team, one the most frequent complaints has been how bad the default “For You” feed view is for following breaking news, something that Twitter (in the pre-Musk days) excelled at.
Threads users routinely mock what seems like a pretty consistent 48 hour delay for event-specific posts, which is especially frustrating as we live through one the most chaotic election years in recent memory.
To try and better understand how much the algorithmic “For You” feed varies from the more straightforward, reverse-chronological “Following” feed, I analyzed 300 posts from both feeds from my Threads account.
No recent posts For You
When I plotted out the age of each post from my “For You” 300 post sample, indeed it does show a chaotic scramble.
If there was an earthquake in your area, and you jumped onto Threads on your phone, the default view you see is “For You,” which includes accounts you don’t follow. Based on my sample, it’s very unlikely any urgent posts on breaking news would show up until hours later.
Over one-third of the posts in my “For You” feed were between six and twelve hours old. Only 12% of the posts happened within an hour of seeing them in my feed. If you really want to follow what the chatter is surrounding a breaking news event, you should be looking at your “Following” feed. Of course, that relies on you having a well-curated list of people who follow and share news.
When I plotted the posts from my “Following” feed, which includes posts from the 954 accounts that I follow, you can see a very different pattern. A clear line of posts going up and to the right, indicating a reverse-chronological series of posts getting older as I scrolled down my feed. 38% of the posts in this feed were posted within an hour, and the vast majority were less than six hours old. Much more useful for breaking news.
Stubborn default settings
Users have been clamoring for a way to control what their default feed view is, but Meta loves the algorithmic feed, so in order to swap views, you need to know where to find the controls for this, which isn't exactly obvious. On mobile, you have to reveal the hidden controls by tapping the Threads logo. It's a bit easier on the web, where you just click on the drop down menu at the top of the feed. On the web, you can also just bookmark https://www.threads.net/following to get straight to the most recent stuff.
Another thing that makes the stubborn initial “For You” feed problematic, is that by default, Threads limits recommending any “political content” from users that you aren't following. You have to dig into your settings to opt-in to see recommended political posts from accounts you don't follow. This decision has been criticized by political observers and creators, especially during this intense election year. The company does not limit political posts in your “Following” feed.
This dataset is admittedly a small sample, of just one account at one moment in time, so your mileage may vary. Meta says that Threads' AI system “blends” content from recommended posts and accounts you follow, and considers your inferred interests and your behavior on the platform to decide what to show you.
But you will have to take Meta's word on it. Earlier this month Meta shuttered its CrowdTangle tool, which provided researchers with a crucial view into what content is shared on Facebook and Instagram. Meta recently released a Threads application programming interface, but right now it mainly enables automated posting and a platform-wide analysis isn't yet possible.
Like the rest of Meta's algorithmic systems, it continues to be a black box.
Meta did not respond to a request for comment.
