Abstract

The massive spread of digital misinformation has been identified as a major threat to democracies. Communication, cognitive, social, and computer scientists are studying the complex causes for the viral diffusion of misinformation, while online platforms are beginning to deploy countermeasures. Little systematic, data-based evidence has been published to guide these efforts. Here we analyze 14 million messages spreading 400 thousand articles on Twitter during ten months in 2016 and 2017. We find evidence that social bots played a disproportionate role in spreading articles from low-credibility sources. Bots amplify such content in the early spreading moments, before an article goes viral. They also target users with many followers through replies and mentions. Humans are vulnerable to this manipulation, resharing content posted by bots. Successful low-credibility sources are heavily supported by social bots. These results suggest that curbing social bots may be an effective strategy for mitigating the spread of online misinformation.

Details

Title
The spread of low-credibility content by social bots
Author
Shao, Chengcheng 1   VIAFID ORCID Logo  ; Ciampaglia, Giovanni Luca 2   VIAFID ORCID Logo  ; Varol, Onur 3   VIAFID ORCID Logo  ; Kai-Cheng, Yang 3 ; Flammini, Alessandro 4 ; Menczer, Filippo 4   VIAFID ORCID Logo 

1  School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA; College of Computer, National University of Defense Technology, Changsha, Hunan, China 
2  Indiana University Network Science Institute, Bloomington, IN, USA 
3  School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA 
4  School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA 
Pages
1-9
Publication year
2018
Publication date
Nov 2018
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41467-018-06930-7
ProQuest document ID
2136225637
Copyright
© 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.