University of Michigan - Ann Arbor

- 245,044 original tweets and 276,418 retweets had toxicity scores 
- Correction increases language toxicity for retweets but not for original tweets 
- Effects of corrections also impact the partisan slant and language toxicity of subsequent tweets besides tweet quality 

Perverse Downstream Consequences of Debunking - RQ3 Language Toxicity

Mosleh, M., Martel, C., Eckles, D., & Rand, D. (2021, May). Perverse Downstream Consequences of Debunking: Being Corrected by Another User for Posting False Political News Increases Subsequent Sharing of Low Quality, Partisan, and Toxic Content in a Twitter Field Experiment. In proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1-13). https://dl.acm.org/doi/10.1145/3411764.3445642 

Perverse Downstream Consequences of Debunking: Being Corrected by Another User for Posting False Political News Increases Subsequent Sharing of Low Quality, Partisan, and Toxic Content in a Twitter Field Experiment

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