activity
20172026
most citedA first look at COVID-19 information and misinformation sharing on Twitter

269 citations · 385 across the 17 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.SI2025

Follow Nudges without Budges: A Field Experiment on Misinformation Followers Didn't Change Follow Networks

Laura Kurek, Joshua Ashkinaze, Ceren Budak +1

Can digital ads encourage users exposed to inaccurate information sources to follow accurate ones? We conduct a large-scale field experiment (N=28,582) on X, formerly Twitter, with…

cs.AI2025

Deep Value Benchmark: Measuring Whether Models Generalize Deep Values or Shallow Preferences

Joshua Ashkinaze, Hua Shen, Saipranav Avula +2

We introduce the Deep Value Benchmark (DVB), an evaluation framework that directly tests whether large language models (LLMs) learn fundamental human values or merely surface-level…

cs.CY2025

Framing Unionization on Facebook: Communication around Representation Elections in the United States

Arianna Pera, Veronica Jude, Ceren Budak +1

Digital media have become central to how labor unions communicate, organize, and sustain collective action. Yet little is known about how unions' online discourse relates to concre…

cs.SI2025

Outsourcing an Information Operation: A Complete Dataset of Tenet Media's Podcasts on Rumble

Laura Kurek, Kevin Zheng, Eric Gilbert +1

Tenet Media, a U.S.-based, right-wing media company, hired six established podcasters to create content related to U.S. politics and culture during the 2024 U.S. presidential elect…

cs.CL2025★ 3 cited

When People are Floods: Analyzing Dehumanizing Metaphors in Immigration Discourse with Large Language Models

Julia Mendelsohn, Ceren Budak

Metaphor, discussing one concept in terms of another, is abundant in politics and can shape how people understand important issues. We develop a computational approach to measure m…