Using co-sharing to identify use of mainstream news for promoting potentially misleading narratives
Pranav Goel (1), Jon Green (2), David Lazer (1, 3), Philip Resnik (4, 5) ((1) Network Science Institute, Northeastern University (2) Department of Political Science, Duke University, (3) Institute for Quantitative Social Science, Harvard University, (4) Department of Linguistics

TL;DR
This study reveals that mainstream news articles are often co-shared with fake news on social media, and that narratives in misinformation are frequently present in co-shared reliable sources, indicating a nuanced form of misinformation.
Contribution
It introduces a novel method to identify misinformation by analyzing co-sharing patterns and narrative overlap between fake news and reliable sources on social media.
Findings
Narratives in misinformation are more likely to appear in co-shared articles.
Users repurpose reliable sources to promote misleading narratives.
Co-sharing patterns reveal a complex misinformation landscape.
Abstract
Much of the research quantifying volume and spread of online misinformation measures the construct at the source level, identifying a set of specific unreliable domains that account for a relatively small share of news consumption. This source-level dichotomy obscures the potential for users to repurpose factually true information from reliable sources to advance misleading narratives. We demonstrate this potentially far more prevalent form of misinformation by identifying articles from reliable sources that are frequently co-shared with (shared by users who also shared) "fake" news on social media, and concurrently extracting narratives present in fake news content and claims fact-checked as false. Specifically in this study, we use Twitter/X data from May 2018 to November 2021 matched to a U.S. voter file. We find that narratives present in misinformation content are significantly…
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Taxonomy
TopicsMisinformation and Its Impacts · Hate Speech and Cyberbullying Detection · Media Influence and Politics
