Concept
Coronavirus goes viral: quantifying the COVID-19 misinformation epidemic on Twitter Data Collection
- Obtained 673 Tweets from the Twitter Archiver add-on search on February 27, 2020 that contained 14 different trending hashtags (446 or 66.6% of the Tweets were from informal accounts and 129 or 19.2% came from verified Twitter accounts)
- Targeted Tweets that had at least one of the 11 common hashtags and 3 keywords that were related to Covid-19 and excluded Tweets with fewer than 4 re-Tweets (hashtags not case sensitive)
- Randomly selected 50 Tweets out of more than 100 Tweets that fit the search criteria
- Categorized the 50 Tweets based on content tone (serious, humorous, opinions) and content type (medical/public health, financial, sociopolitical)
- Compared Tweets with information obtained from WHO, CDC, peer-reviewed scientific journals, and prominent new outlets to identify any potential misinformation
- If information presented in a Tweet cannot be verified using these sources, it is considered unverifiable rather than misinformative
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Updated 2021-01-28
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CSCW (Computer-supported cooperative work)
Computing Sciences