ArticleScience advances2026
Community Notes undermoderate polarizing content by design creating risks in electoral processes.
Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
0 citing papers in PubMed.
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Community Notes of X enables users to collaboratively moderate misleading content. To resolve conflicting moderation, Community Notes infers a latent ideological dimension and selects notes garnering cross-partisan support. As this system is now deployed worldwide, we evaluate its operation across diverse polarization contexts. We analyze all 1.9 million moderation notes receiving 135 million ratings by March 2025, cross-referencing ideological scaling data on 13 countries. Our results show that the Community Notes algorithm effectively captures the main polarizing dimensions across countries, surfacing notes that garner cross-partisan support. This also means that, by design, Community Notes systematically undermoderate polarizing content. We analyze notes relating to four recent elections in the United States (2024), the United Kingdom (2024), France (2024), and Germany (2025) and demonstrate that they are systematically undermoderated when compared to other notes, posing potential risks to civic discourse and electoral processes.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.