Differential impact from individual versus collective misinformation tagging on the diversity of Twitter (X) information engagement and mobility

Junsol Kim, Zhao Wang, Haohan Shi, Hsin-Keng Ling and James Evans ()
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Junsol Kim: University of Chicago
Zhao Wang: University of Chicago
Haohan Shi: Northwestern University
Hsin-Keng Ling: University of Michigan
James Evans: University of Chicago

Nature Communications, 2025, vol. 16, issue 1, 1-14

Abstract: Abstract Fears about the destabilizing impact of misinformation online have motivated individuals and platforms to respond. Individuals have increasingly challenged others’ online claims with fact-checks in pursuit of a healthier information ecosystem and to break down echo chambers of self-reinforcing opinion. Using Twitter (now X) data, here we show the consequences of individual misinformation tagging: tagged posters had explored novel political information and expanded topical interests immediately prior, but being tagged caused posters to retreat into information bubbles. These unintended consequences were softened by a collective verification system for misinformation moderation. In Twitter’s new feature, Community Notes, misinformation tagging was peer-reviewed by other fact-checkers before revelation to the poster. With collective misinformation tagging, posters were less likely to retreat from diverse information engagement. Detailed comparison demonstrated differences in toxicity, sentiment, readability, and delay in individual versus collective misinformation tagging messages. These findings provide evidence for differential impacts from individual versus collective moderation strategies on the diversity of information engagement and mobility across the information ecosystem.

Date: 2025
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DOI: 10.1038/s41467-025-55868-0

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