Concept
“I Won the Election!”: An Empirical Analysis of Soft Moderation Interventions on Twitter Data Collection
- Used Twitter API to get tweets and retweets from verified users on Twitter because they have a larger following, as well as information regarding whether a tweet has warning labels
- Between December 7th to 31st, 2020, researchers obtained a total of 79,361,081 tweets from 168,126 verified users
- To obtain tweets with warning labels, tweets that quote other tweets containing warning labels, and retweets of tweets with warning labels, researchers again used Twitter API
- Final dataset consisted of 18,765 tweets containing warning labels from 8,142 users
- Divided dataset into two groups – tweets with warning labels and tweets quoting other tweets with warning labels
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Updated 2021-05-18
Tags
CSCW (Computer-supported cooperative work)
Computing Sciences
Learn After
“I Won the Election!”: An Empirical Analysis of Soft Moderation Interventions on Twitter Analysis of RQ1 - warnings labels and users
“I Won the Election!”: An Empirical Analysis of Soft Moderation Interventions on Twitter Analysis of RQ2 - engagement analysis
“I Won the Election!”: An Empirical Analysis of Soft Moderation Interventions on Twitter Analysis of RQ3 - user interaction with tweets containing warning labels