activity
20242026
most citedWikipedia in Wartime: Experiences of Wikipedians Maintaining Articles About the Russia-Ukraine War

5 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Information Discernment in Large Language Models

Joshua Ashkinaze, Laura Kurek, Alina Faisal +4

LLMs are increasingly used with external knowledge sources like the internet. Do they weigh information appropriately -- updating more for reliable sources (source discernment) and…

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.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.SI2024★ 5 cited

Wikipedia in Wartime: Experiences of Wikipedians Maintaining Articles About the Russia-Ukraine War

Laura Kurek, Ceren Budak, Eric Gilbert

How do Wikipedians maintain an accurate encyclopedia during an ongoing geopolitical conflict where state actors might seek to spread disinformation or conduct an information operat…

cs.CL2024

Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms

Joshua Ashkinaze, Ruijia Guan, Laura Kurek +3

Large language models (LLMs) are trained on broad corpora and then used in communities with specialized norms. Is providing LLMs with community rules enough for models to follow th…