Often built on outrage and clickbait, social media can fuel misinformation and further entrench divisions between users on opposite political spectrums. 

But what if these platforms could help us bridge divides? University of Michigan School of Information professor Paul Resnick, an expert on social media and machine learning, says we may be able to use algorithms to foster understanding instead of polarization. 

“I think what we have to do is accept that yes, the outrageous stuff is engaging, and the stuff that makes our blood boil is engaging, but that might not be the only thing that engages us,” he says. “If you had an algorithm that could identify the pearls of wisdom someone I don’t agree with has, and some of the things that they’re seeing that I don’t see, I think some of those things are things that I would also engage with and not in quite such a negative way. That’s the hope.”

Currently a 2024/2025 visiting scholar at the Institute for Rebooting Social Media at Harvard University’s Berkman Klein Center for Internet & Society, Resnick is looking at the effectiveness of X’s community notes tool. The feature allows users to add context to potentially misleading posts, and shows up when enough contributors from different points of view rate that note as helpful.

“It comes back to the civic broccoli idea,” Resnick says. “Can we make connecting and bridging across these ideological differences be ice cream instead of broccoli?”

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Listen “How Systems Like Community Notes on Twitter/X Aim to Break the Cycle of Misinformation” at the Outrage Overload podcast. 

Paul Resnick is the Michael D Cohen Collegiate Professor of Information and a Professor of Information at UMSI. Learn more about him by visiting his UMSI faculty profile.