Jon Green

Jon Green

Assistant Professor, Duke University

Selected Publications

You can also find publications on my Google Scholar profile.

Using co-sharing to identify use of mainstream news for promoting potentially misleading narratives

Nature Human Behavior, 2025

Uses co-sharing behavior and narrative extraction to identify cases of true information from reliable sources being strategically repurposed to promote potentially misleading narratives.

Recommended citation: Goel, Pranav, Jon Green, David Lazer, and Philip Resnik. 2025. "Using co-sharing to identify use of mainstream news for promoting potentially misleading narratives." Nature Human Behavior.
External link

Meet the Press: Gendered Conversational Norms in Televised Political Discussions

Journal of Politics, 2025

Testing relationships between gender composition, conversational norms, and participatory equality in televised political discussions.

Recommended citation: Naftel, Daniel, Jon Green, Kelsey Shoub, Jared Edgerton, Mallory Wagner, and Skyler Cranmer. 2025. "Meet the Press: Gendered Conversational Norms in Televised Political Discussion." Journal of Politics, 87(3)
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Curation Bubbles

American Political Science Review, 2025

Aligning theory and measurement in political information sharing on social media.

Recommended citation: Green, Jon, Stefan McCabe, Sarah Shugars, Hanyu Chwe, Luke Horgan, Shuyang Cao, and David Lazer. 2025. "Curation Bubbles." American Political Science Review, FirstView.
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Inequalities in Online Representation: Who follows their own member of Congress on Twitter?

Journal of Quantitative Description: Digital Media, 2023

Finds that Twitter users who follow their own member of Congress are older, live in wealthier areas of their district, and are more politically and demographically similar to the member than users who do not.

  • Recipient of the 2024 Best Article award from the Information Technology & Politics section of the American Political Science Association.

Recommended citation: McCabe, Stefan, Jon Green, Pranav Goel, and David Lazer. 2023. "Inequalities in Online Representation: Who follows their own member of Congress on Twitter?." Journal of Quantitative Description: Digital Media, 3.
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Something to Run For: Stated Motives as Indicators of Candidate Emergence

Political Behavior, 2023

Finds that prospective candidates for state and local office who articulated their interest in localized and goal-congruent terms were likelier to actually run for office than those who articulated their interest in more general or nationalized terms.

Recommended citation: Green, Jon, Meredith Conroy, and Ciera Hammond. 2023. "Something to Run For: Stated Motives as Indicators of Candidate Emergence." Political Behavior.
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Users choose to engage with more partisan news than they are exposed to on Google Search

Nature, 2023

Finds limited evidence that users’ search results systematically differ by user partisanship, but stronger evidence that users’ engagement with search results does.

Recommended citation: Robertson, Ronald E., Jon Green, Damian Ruck, Katherine Ognyanova, Christo Wilson, and David Lazer. 2023. "Users choose to engage with more partisan news than they are exposed to on Google Search." Nature 618: 342-348.
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Machine Learning for Experiments in the Social Sciences

Cambridge University Press, Elements Series in Experimental Political Science, 2023

A practical introduction to machine learning for readers who are familiar with experiments.

Recommended citation: Green, Jon, and Mark H. White II. 2023. Machine Learning for Experiments in the Social Sciences. Cambridge University Press, Elements Series in Experimental Political Science.
External link

Online Engagement with 2020 Election Misinformation and Turnout in the 2021 Georgia Runoff Election

Proceedings of the National Academy of Sciences, 2022

Finds relationships between public engagement with 2020 election conspiracy theories on Twitter and turnout in the 2021 Georgia runoff election.

Recommended citation: Green, Jon, William Hobbs, Stefan McCabe, and David Lazer. 2022. "Online Engagement with 2020 Election Misinformation and Turnout in the 2021 Georgia Runoff Election." Proceedings of the National Academy of Sciences 119(34): e2115900119.
External link