Nieman Foundation at Harvard
HOME
          
LATEST STORY
From shrimp Jesus to fake self-portraits, AI-generated images have become the latest form of social media spam
ABOUT                    SUBSCRIBE
Oct. 7, 2021, 1:34 p.m.
LINK: twitter.com  ➚   |   Posted by: Laura Hazard Owen   |   October 7, 2021

On August 3, 2018, Facebook went down for 45 minutes. That’s a little baby outage compared to the one this week, when, on October 4, Facebook, Instagram, and WhatsApp were down for more than five hours. Three years ago, the 45-minute Facebook break was enough to get people to go read news elsewhere, Chartbeat‘s Josh Schwartz wrote for us at the time.

So what happened this time around? For a whopping five-hours-plus, people read news, according to data Chartbeat gave us this week from its thousands of publisher clients across 60 countries.. (And they went to Twitter; Chartbeat saw Twitter traffic up 72%. If Bad Art Friend had been published on the same day as the Facebook outage, Twitter would have literally exploded, presumably.)

At the peak of the outage — around 3 p.m. ET — net traffic to pages across the web was up by 38% compared to the same time the previous week, Chartbeat found.

By the way, here’s how Chartbeat defines direct traffic and dark social, from CMO Jill Nicholson.

And here’s a question a bunch of people had. We’ll update this post when we know!

Show tags
 
Join the 60,000 who get the freshest future-of-journalism news in our daily email.
From shrimp Jesus to fake self-portraits, AI-generated images have become the latest form of social media spam
Within days of visiting the pages — and without commenting on, liking, or following any of the material — Facebook’s algorithm recommended reams of other AI-generated content.
What journalists and independent creators can learn from each other
“The question is not about the topics but how you approach the topics.”
Deepfake detection improves when using algorithms that are more aware of demographic diversity
“Our research addresses deepfake detection algorithms’ fairness, rather than just attempting to balance the data. It offers a new approach to algorithm design that considers demographic fairness as a core aspect.”