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, James Evans

TL;DR
This study examines how individual and collective misinformation tagging on Twitter differently affect user engagement, information diversity, and mobility, highlighting the benefits of collective verification systems in reducing echo chambers.
Contribution
It provides empirical evidence that collective misinformation tagging moderates user retreat into echo chambers more effectively than individual tagging.
Findings
Individual tagging leads to user retreat into information bubbles.
Collective tagging reduces user retreat and promotes diverse engagement.
Differences observed in toxicity, sentiment, readability, and delay between tagging methods.
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…
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Taxonomy
TopicsMisinformation and Its Impacts · Social Media and Politics · Hate Speech and Cyberbullying Detection
