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
May 27, 2014, 10:31 a.m.
Audience & Social
LINK: qz.com  ➚   |   Posted by: Caroline O'Donovan   |   May 27, 2014

BuzzFeed announced to partners that they’ll be turning away from their traffic partner network, powered through the site fre.sh but largely driven through headline modules on BuzzFeed itself. Quartz’s John McDuling explains what its value was to publishers and to BuzzFeed — traffic and data, respectively:

About 200 websites (including, briefly, Quartz) signed up to get traffic from BuzzFeed through its fre.sh website and headline modules on BuzzFeed itself, a program which has been active for about five years. The New Statesman had a good explanation for how the website worked. BuzzFeed would link to the websites of publishers that signed up, in exchange for being able to track information about traffic from those publishers. “BuzzFeed now knows how many of its readers also click around the Daily Mail, and how many of them get their ‘real’ news from the Guardian. All that data pays back back to the site’s native advertising model,” the Statesman wrote.

Though Quartz was a participant, it seems that the loss won’t hit them very hard:

BuzzFeed will now be “shifting the structure of the partner network to a select group of new partners, solely focused around video.”

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.”