2023
DOI: 10.2196/preprints.45686
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Looking back to the future: Unpacking the first nine months of the novel COVID-19 infodemic on Twitter with a content analysis (Preprint)

Abstract: UNSTRUCTURED This study analyzed 25,018,086 tweets posted during the initial nine months of the COVID-19 pandemic between March to November 2020. Using a mixed method of automated (i.e., LDA topic model) and manual content analyses, results from this study point to debatable information as the most prevalent and diffused information category followed by credible information, general disinformation, trolling, biased or one-sided and conspiratorial disinformation. Contrary to mainstream u… Show more

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