Concept

Characterizing COVID-19 Misinformation Communities Using a Novel Twitter Dataset communities

Two communities were derived using the annotated tweets. A valence value of +1 was given to the categories of annotated tweets that fall into "True Treatment", "True Prevention", "Correction/Calling Out", "Sarcasm/Satire", and "True Public Health Response", and a valence value of -1 was given to the categories of annotated tweets that fall into "Conspiracy," "Fake Cure", "Fake Treatment", "False Fact or Prevention", and "False Public Health Response." Users' valence values are calculated and placed into three groups: >0 "informed", <0 misinformed, and 0 "ambiguous."

Of the 3629 users, 1697 (47%) were placed into the informed group, 1043 (29%) were placed into the misinformed group, and 889 (24%) were ambiguous.

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Updated 2021-01-28

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CSCW (Computer-supported cooperative work)

Computing Sciences