Community-Based Fact-Checking on Twitter's Birdwatch Platform
Researchers studied how Twitter users engage with the new feature Birdwatch that allows users to address misinformation.
- RQ 1: What are specific reasons due to which Birdwatch users report tweets?
- RQ 2: How do Birdwatch notes for tweets categorized as being misleading vs. not misleading differ in terms of their content characteristics? (e.g. sentiment, length)
- RQ 3: Are tweets from Twitter accounts with certain characteristics (e.g. politicians, accounts with many followers) more likely to be fact-checked on Birdwatch?
- RQ 4: Which characteristics of Birdwatch notes are associated with greater helpfulness for other users?
- RQ 5: Does the level of consensus between users vary depending on the level of social influence of the source tweet?
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CSCW (Computer-supported cooperative work)
Computing Sciences
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Learn After
Community-Based Fact-Checking on Twitter's Birdwatch Platform
Community-Based Fact-Checking on Twitter's Birdwatch Platform - Birdwatch
Community-Based Fact-Checking on Twitter's Birdwatch Platform - Methodology
Community-Based Fact-Checking on Twitter's Birdwatch Platform - Analysis
Community-Based Fact-Checking on Twitter's Birdwatch Platform - Results
Community-Based Fact-Checking on Twitter's Birdwatch Platform - Discussion