269 citations · 385 across the 17 of their papers we have counts for
6 papers · 1 filter
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…
Plurals: A System for Guiding LLMs Via Simulated Social Ensembles
Joshua Ashkinaze, Emily Fry, Narendra Edara +2
Recent debates raised concerns that language models may favor certain viewpoints. But what if the solution is not to aim for a 'view from nowhere' but rather to leverage different…
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…
Framing Social Movements on Social Media: Unpacking Diagnostic, Prognostic, and Motivational Strategies
Julia Mendelsohn, Maya Vijan, Dallas Card +1
Social media enables activists to directly communicate with the public and provides a space for movement leaders, participants, bystanders, and opponents to collectively construct…
The Dynamics of (Not) Unfollowing Misinformation Spreaders
Joshua Ashkinaze, Eric Gilbert, Ceren Budak
Many studies explore how people 'come into' misinformation exposure. But much less is known about how people 'come out of' misinformation exposure. Do people organically sever ties…
How AI Ideas Affect the Creativity, Diversity, and Evolution of Human Ideas: Evidence From a Large, Dynamic Experiment
Joshua Ashkinaze, Julia Mendelsohn, Li Qiwei +2
Exposure to large language model output is rapidly increasing. How will seeing AI-generated ideas affect human ideas? We conducted an experiment (800+ participants, 40+ countries)…