Social media research tool lowers the political temperature | Stanford Report

In an experiment using the tool with about 1,200 participants over 10 days during the 2024 election, those who had antidemocratic content downranked showed more positive views of the opposing party. The effect was also bipartisan, holding true for people who identified as liberals or conservatives.

“Social media algorithms directly impact our lives, but until now, only the platforms had the ability to understand and shape them,” said Michael Bernstein, a professor of computer science in Stanford’s School of Engineering and the study’s senior author. “We have demonstrated an approach that lets researchers and end users have that power.”

The tool could also open ways to create interventions that not only mitigate partisan animosity, but also promote greater social trust and healthier democratic discourse across party lines, added Bernstein, who is also a senior fellow at the Stanford Institute for Human-Centered Artificial Intelligence.

The impact on polarization was clear, said Piccardi, who is now an assistant professor of computer science at Johns Hopkins University.

“When the participants were exposed to less of this content, they felt warmer toward the people of the opposing party,” he said. “When they were exposed to more, they felt colder.”