🤖 AI Summary
This study investigates a covert yet prevalent misinformation propagation mechanism: how users strategically cite authentic content from mainstream news to lend credibility to misleading narratives. Method: Leveraging cross-platform matched data—Twitter/X posts (2018–2021) and U.S. voter records—combined with social co-occurrence network analysis, narrative extraction, and alignment with fact-checking labels, the study systematically identifies high-frequency credible source articles co-circulated with misinformation. Contribution/Results: Moving beyond the binary “source reliability = content credibility” assumption, the study provides empirical evidence that, within the same reputable source, articles co-shared with misinformation contain significantly higher rates of misleading narratives than non-co-shared control articles (p < 0.01). Findings reveal that mainstream news is being instrumentalized to enhance the legitimacy and diffusion efficacy of false claims, uncovering “authentic-content appropriation” as a critical pathway in the contemporary misinformation ecosystem.
📝 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 more likely to occur in co-shared articles than in articles from the same reliable sources that are not co-shared, consistent with users using information from mainstream sources to enhance the credibility and reach of potentially misleading claims.
