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Governing Generative Echo Chambers: Cultural Polarization Across AI and Platform Regulation

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.telpol.2025.102917openalex-snapshot
It's just distributed computing: Rethinking AI governance
inferredcites →https://doi.org/10.1016/j.telpol.2025.103088openalex-snapshot
Big data, small answers: How the DSA Transparency Database falls short of its regulatory objectives
inferredcites →https://doi.org/10.1073/pnas.2311627120openalex-snapshot
Leveraging AI for democratic discourse: Chat interventions can improve online political conversations at scale
inferredcites →https://doi.org/10.1093/poq/nfw006openalex-snapshot
Filter Bubbles, Echo Chambers, and Online News Consumption
inferredcites →https://doi.org/10.1145/3544548.3581196openalex-snapshot
Co-Writing with Opinionated Language Models Affects Users’ Views
inferredcites →https://doi.org/10.1145/3613904.3642322openalex-snapshot
AI-Driven Mediation Strategies for Audience Depolarisation in Online Debates
inferredcites →https://doi.org/10.1145/3613904.3642459openalex-snapshot
Generative Echo Chamber? Effect of LLM-Powered Search Systems on Diverse Information Seeking
inferredcites →https://doi.org/10.1145/3706598.3713564openalex-snapshot
AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances
inferredcites →https://doi.org/10.1609/icwsm.v19i1.35826openalex-snapshot
Understanding Online Polarization Through Human-Agent Interaction in a Synthetic LLM-Based Social Network
inferredcites →https://doi.org/10.18653/v1/2023.emnlp-main.148openalex-snapshot
The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Values
inferredcites →https://doi.org/10.18653/v1/2024.acl-long.671openalex-snapshot
Investigating Cultural Alignment of Large Language Models
inferredcites →https://doi.org/10.18653/v1/2024.acl-long.862openalex-snapshot
Having Beer after Prayer? Measuring Cultural Bias in Large Language Models
inferredcites →https://doi.org/10.52202/068431-2766openalex-snapshot
Fine-Tuning Language Models to Find Agreement Among Humans with Diverse Preferences
inferredcites →https://doi.org/10.52202/079017-3342openalex-snapshot
The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models
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