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https://pubmed.ncbi.nlm.nih.gov/38117843
This study combines machine learning and qualitative content coding to analyze conspiracy discourse related to 5G and COVID-19 on Twitter, finding that conspiracy-related discourse is more likely to express negative emotions and use combatant language, while corrections discourse is more likely to use prosocial language and reference health consequences.