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Incentivizing News Consumption on Social Media Platforms Using Large Language Models and Realistic Bot Accounts
March 21, 2024, 4:48 a.m. | Hadi Askari, Anshuman Chhabra, Bernhard Clemm von Hohenberg, Michael Heseltine, Magdalena Wojcieszak
cs.CL updates on arXiv.org arxiv.org
Abstract: Polarization, declining trust, and wavering support for democratic norms are pressing threats to U.S. democracy. Exposure to verified and quality news may lower individual susceptibility to these threats and make citizens more resilient to misinformation, populism, and hyperpartisan rhetoric. This project examines how to enhance users' exposure to and engagement with verified and ideologically balanced news in an ecologically valid setting. We rely on a large-scale two-week long field experiment (from 1/19/2023 to 2/3/2023) on …
abstract arxiv bot consumption cs.ai cs.cl cs.si democracy democratic language language models large language large language models media misinformation platforms quality resilient social social media social media platforms support threats trust type
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