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  4. 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

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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sword-2022-09-08T15:16:31.original.xml (130 B)
Original SWORD entry document
Author(s)
Mosleh, Mohsen
•
Martel, Cameron
•
Eckles, Dean
•
Rand, David
Date Issued
2021
Journal
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Publisher
Association for Computing Machinery (ACM)
Citation
Mosleh, Mohsen, Martel, Cameron, Eckles, Dean and Rand, David. 2021. "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." Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems.
Version
Author's final manuscript
MIT Department
Sloan School of Management
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/145320
DOI of Published Version
https://doi.org/10.1145/3411764.3445642
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