COVID-19 misinformation and the 2020 U.S. presidential election-Reference-Cited by-同舟云学术

COVID-19 misinformation and the 2020 U.S. presidential election

Published:2021-03-03 Issue: Volume: Page:
ISSN:
Container-title:Harvard Kennedy School Misinformation Review
language:
Short-container-title:HKS Misinfo Review

Author:

Chen Emily¹,Chang Herbert²,Rao Ashwin³,Lerman Kristina¹,Cowan Geoffrey²,Ferrara Emilio²

Affiliation:

1. Information Sciences Institute, University of Southern California, USA

2. Annenberg School for Communication and Journalism, University of Southern California, USA

3. Information Sciences Institute, University of Southern California, USA,

Abstract

Voting is the defining act for a democracy. However, voting is only meaningful if public deliberation is grounded in veritable and equitable information. This essay investigates the politicization of public health practices during the Democratic primaries in the context of the 2020 U.S. presidential election, using a dataset of more than 67 million tweets. We find the public sphere on Twitter is politically heterogeneous and the majority—liberal and conservative alike—advocates for wearing masks and vote-by-mail. However, a small, but dense group of conservative users push anti-mask and voter fraud narratives.

Funder

Defense Advanced Research Projects Agency

Air Force Office of Scientific Research

Publisher

Shorenstein Center for Media, Politics, and Public Policy

Reference36 articles.

1. As U.S. Coronavirus cases hit 3.5 million, officials scramble to add restrictions. (2020, July 15). The New York Times. https://www.nytimes.com/2020/07/15/world/coronavirus-updates.html

2. Badawy, A., Lerman, K., & Ferrara, E. (2019, May). Who falls for online political manipulation? Companion Proceedings of the 2019 World Wide Web Conference (pp. 162-168). https://doi.org/10.1145/3308560.3316494

3. Bessi, A. & Ferrara, E. (2016). Social bots distort the 2016 us presidential election online discussion. First Monday, 21(11-7). http://dx.doi.org/10.5210/fm.v21i11.7090

4. Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. The Journal of Machine Learning Research, 3, 993–1022. https://jmlr.org/papers/volume3/blei03a/blei03a.pdf

5. Bogage, J., Rein, L., & Dawsey, J. (2020, August 20). Postmaster general eyes aggressive changes at Postal Service after election. The Washington Post. https://www.washingtonpost.com/business/2020/08/20/us-postal-service-louis-dejoy/

Cited by 45 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. COVID-19 anti-vaccine misinformation discourse on Twitter: Influential roles of polarization and the 2020 US presidential election;Telematics and Informatics Reports;2024-09

2. Automated Claim Matching with Large Language Models: Empowering Fact-Checkers in the Fight Against Misinformation;Companion Proceedings of the ACM Web Conference 2024;2024-05-13

3. Wording Matters: the Effect of Linguistic Characteristics and Political Ideology on Resharing of COVID-19 Vaccine Tweets;ACM Transactions on Computer-Human Interaction;2024-01-30

4. Right-Wing Authoritarian Attitudes, Fast-Paced Decision-Making, and the Spread of Misinformation About COVID-19 Vaccines;Political Communication;2023-12-20

5. Peer correction of misinformation on social media: (In)civility, success experience and relationship consequences;New Media & Society;2023-11-20