25 citations · 46 across the 9 of their papers we have counts for
9 papers
How Human Feedback Shapes AI-generated Community Notes
Soham De, Isaac Slaughter, Jiawei Guo +4
Community Notes, a bridging-based crowd-sourced fact-checking system, has emerged as a new mechanism for moderating misleading information on social media and has been adopted by m…
Detecting and Enhancing Intellectual Humility in Online Political Discourse
Samantha D'Alonzo, Rachel Chen, Weidong Zhang +7
Intellectual humility (IH)-a recognition of one's own intellectual limitations-can reduce polarization and foster more understanding across lines of difference. Yet little work exp…
The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagement
Jonathan Stray, Ian Baker, George Beknazar-Yuzbashev +41
We report the first direct comparisons of multiple alternative social media algorithms on multiple platforms on outcomes of societal interest. We used a browser extension to modify…
Grok in the Wild: Characterizing the Roles and Uses of Large Language Models on Social Media
Katelyn Xiaoying Mei, Robert Wolfe, Nicholas Weber +1
xAI's large language model, Grok, is called by millions of people each week on the social media platform X. Prior work characterizing how large language models are used has focused…
Scaling Human Judgment in Community Notes with LLMs
Haiwen Li, Soham De, Manon Revel +6
This paper argues for a new paradigm for Community Notes in the LLM era: an open ecosystem where both humans and LLMs can write notes, and the decision of which notes are helpful e…
Community notes reduce engagement with and diffusion of false information online
Isaac Slaughter, Axel Peytavin, Johan Ugander +1
Social networks scaffold the diffusion of information on social media. Much attention has been given to the spread of true vs. false content on online social platforms, including t…
Supernotes: Driving Consensus in Crowd-Sourced Fact-Checking
Soham De, Michiel A. Bakker, Jay Baxter +1
X's Community Notes, a crowd-sourced fact-checking system, allows users to annotate potentially misleading posts. Notes rated as helpful by a diverse set of users are prominently d…
Reranking partisan animosity in algorithmic social media feeds alters affective polarization
Tiziano Piccardi, Martin Saveski, Chenyan Jia +3
Today, social media platforms hold sole power to study the effects of feed ranking algorithms. We developed a platform-independent method that reranks participants' feeds in real-t…
Reranking Social Media Feeds: A Practical Guide for Field Experiments
Tiziano Piccardi, Martin Saveski, Chenyan Jia +3
Social media plays a central role in shaping public opinion and behavior, yet performing experiments on these platforms and, in particular, on feed algorithms is becoming increasin…