Study: X algorithm amplifies 'ragebait' content, Democrats see more

The study, conducted by researchers including Stanford's Ziv Epstein, tracked 715 American X users who installed a browser extension that collected their For You and Following feeds. Participants completed a "values inventory" based on the Schwartz Theory of Basic Values, which breaks belief systems into 19 points such as "tolerance" and "dominance," and reported their political alignments.

The researchers found that the algorithm was "more likely to amplify" content that did not align with users' self-reported values, meaning users quickly began seeing posts that angered them. Epstein told 404 Media that the findings are "not the most surprising headline ever," but the team wanted to understand the mechanism. "X's feed algorithm, like a lot of these social media algorithms, is optimized for engagement [but] it turns out that not all types of engagement are considered equally," he said.

Explaining the feedback loop, Epstein noted that replying to a post is weighted much more heavily than liking, even though replies account for under seven percent of interactions on the platform. "Replying is only a fraction of engagement, but there does seem to be some evidence that these algorithms are prioritizing and learning more from this kind of rarer form of engagement," he said. "So it's this feedback loop of outrage baiting. The algorithm learns that you get outraged and then continues to serve more content in that direction."

The study also found that ragebait content was served more to users who identified as Democrats. The researchers said they do not yet have a conclusive reason, suggesting it could be because there is simply more right-wing content on X, or that Democrats tend to engage more with posts they disagree with.

X has not formally responded to the research. However, Nikita Bier, the company's former head of product, wrote on the platform that the algorithm has been adjusted since the study took place, reducing ragebait content "by order [sic] of magnitude." The study and Bier's claim point to ongoing concerns about how social media algorithms shape the information users consume, with Epstein emphasizing the lack of transparency around these systems.