Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter

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Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter

On July 27, 2020, former US President Donald Trump retweeted to his then 84 million
Twitter followers an online video, published by the Breitbart website, promoting misinformation
about the anti-malarial drug, hydroxychloroquine.1 The video, featuring Dr Stella
Immanuel and a group called America’s Frontline Doctors, falsely claimed that the
combination of hydroxychloroquine, zinc, and azithromycin (an antibiotic) could cure
COVID-19.1 Twitter subsequently removed President Trump’s retweet, temporarily suspended
and removed tweets from his son, Donald Trump Jr, and removed and suspended other
accounts sharing this false information as a violation of its COVID-19 misinformation
policy.

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