Solomon Messing
Solomon Messing is a data scientist who studies how algorithms and online information shape what people think about politics. He founded Pew Research Center’s Data Labs and has worked as a research scientist at Facebook and Twitter, and as chief scientist at Acronym. He is now a Research Associate Professor at New York University.
His work on media polarization and filter bubbles, published in Science, helped spark discussions about how networks and algorithms influence the media. He also explored how people understand election forecasts, contributing to public debate; FiveThirtyEight’s Politics Podcast cited his ideas when it switched how it presented forecasts from percent chances to odds.
Messing led Facebook’s effort to release a very large social media research dataset, using differential privacy to protect user data.
He earned a PhD in 2013 and a master’s degree in Statistics from Stanford University.
This page was last edited on 2 February 2026, at 14:35 (CET).