Jenny Allen

@jennyallen.bsky.social

Assistant Professor of Technology, Operations, and Statistics @ NYU Stern Interested in Computational Social Science, Digital Persuasion, and Wisdom of Crowds

1/ Excited to report we have a new paper out @nature.com today! The bottom line: training data for LLMs does not just fall from the sky - it is created in the context of existing social political institutions - and that has consequences for LLM output. nature.com/articles/s41...

State media control influences large language models - Nature

Government-controlled media influences the output of large language models via their training data, and models queried in the languages of countries with lower media freedom show a stronger ...

nature.com

New in Nature: LLMs give "the party line" in the languages of authoritarian regimes. This works when they control the media, which feeds pretraining data. We show more state control over the media means less critical LLMs. 6 studies spanning 38 languages & 13 models. Details ↓

Scatter plot of 38 countries plus China showing the proportion of LLM responses favorable to the regime in the local language vs. World Press Freedom Index score. Lower press freedom predicts more regime-favorable responses; all production models pooled.

🥁🥁🥁 Newly out from us today in Science Advances: “Biased AI Writing Assistants Shift Users’ Attitudes on Societal Issues”. Large Language Models are providing users with autocomplete writing suggestions on many platforms. Could these suggestions shift users’ own attitudes? (spoiler: YES) (1/7)

Last week the story was that TikTok censored anti-Trump/ICE/Pretti videos after the U.S. ownership change. We investigated with a large set of US TikTok data and found some interesting results, short thread...

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New paper in Science: In a platform-independent field experiment, we show that reranking content expressing antidemocratic attitudes and partisan animosity in social media feeds alters affective polarization. 🧵

Today, social media platforms hold the sole power to study the effects of feed-ranking algorithms. We developed a platform-independent method that reranks participants’ feeds in real time and used this method to conduct a preregistered 10-day field experiment with 1256 participants on X during the 2024 US presidential campaign. Our experiment used a large language model to rerank posts that expressed antidemocratic attitudes and partisan animosity (AAPA). Decreasing or increasing AAPA exposure shifted out-party partisan animosity by more than 2 points on a 100-point feeling thermometer, with no detectable differences across party lines, providing causal evidence that exposure to AAPA content alters affective polarization. This work establishes a method to study feed algorithms without requiring platform cooperation, enabling independent evaluation of ranking interventions in naturalistic settings.

🚨Out in PNAS🚨 Examining news on 7 platforms: 1)Right-leaning platforms=lower quality news 2)Echo-platforms: Right-leaning news gets more engagement on right-leaning platforms, vice-versa for left-leaning 3)Low-quality news gets more engagement EVERYWHERE - even BlueSky! www.pnas.org/doi/10.1073/...

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"While high-quality content is posted more and receives more total engagement across platforms...a given author attracts higher levels of engagement when they post lower-quality content" "pattern we find seems to be driven more by an underperformance of particularly popular high-quality outlets"

Divergent patterns of engagement with partisan and low-quality news across seven social media platforms | PNAS

In recent years, social media has become increasingly fragmented, as platforms evolve and new alternatives emerge. Yet most research studies a sing...

pnas.org

📣 Yale workshop, Oct 16-17! 📣 How could/should content ranking work? What's new in content moderation? How can platforms promote civility? Hosted by Yale's Institute for Foundations of Data Science (FDS). Great speakers! Submit posters by 9/22! Spread the word! yalefds.swoogo.com/socialalgori...

New Directions in Social Algorithms Research on October 16-17, 2025 at Yale University

As social media algorithms increasingly mediate social experiences, there has been a rapid increase in research on the effects of how these algorithms are configured, alternatives to engagement-centri...

yalefds.swoogo.com

New WP! The illusory truth effect (repetition -> belief) is core to psych of beliefs, & thought to be a deep bias impacting misinfo, persuasion & advertising Why would cognition include such a flaw? We argue it is a rational adaptation to high-quality info environments 🧵1/

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🚨New WP🚨 We examine news sharing on 7 platforms: 1)Right-leaning platforms=lower quality news 2)Echo-platforms: Right-leaning news gets more engagement on right-leaning platforms, vice-versa for left-leaning 3)But low-quality news gets more engagement EVERYWHERE, even BlueSky! osf.io/preprints/ps...

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