logo
How it worksCoursesResearch CommunitiesBenefitsAbout Us
Schedule Demo
Learn Before
Concept

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

  • the misinformed community is more dense than the informed community
  • the reply network has much greater communication between the two groups than the retweet or mention network
  • the percentage of bots in the misinformed community (19%) is higher than the percentage of bots in the informed community (14%)
  • bots may indicate a spread of disinformation
  • informed users use more narratives as they use more pronouns, functional words, and family-related words
  • there is no significant difference in tone between the two communities; both are highly negative
  • misinformed users tend to be more informal than informed users, but informed users use more swear words
  • many in the misinformed community are anti-vaxxers with 41% being so and 22% being anti-vaxxer bots

0

1

Updated 2021-01-28

Contributors are:

Rachel Wong
Rachel Wong
🏆 1

Who are from:

University of California, Berkeley
University of California, Berkeley
🏆 1

References

Tags

CSCW (Computer-supported cooperative work)

Computing Sciences

Related