This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2388) Infodemiology and Infoveillance (1269) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1552) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1010) Quality/Credibility of eHealth Information and Trust Issues (485) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1481) Outbreak and Pandemic Preparedness and Management (1673)

Published on in Vol 23, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26692, first published .
Political Partisanship and Antiscience Attitudes in Online Discussions About COVID-19: Twitter Content Analysis

Political Partisanship and Antiscience Attitudes in Online Discussions About COVID-19: Twitter Content Analysis

Political Partisanship and Antiscience Attitudes in Online Discussions About COVID-19: Twitter Content Analysis

Authors of this article:

Ashwin Rao1 Author Orcid Image ;   Fred Morstatter1 Author Orcid Image ;   Minda Hu1 Author Orcid Image ;   Emily Chen1 Author Orcid Image ;   Keith Burghardt1 Author Orcid Image ;   Emilio Ferrara1 Author Orcid Image ;   Kristina Lerman1 Author Orcid Image
Article Authors Cited by (30) Tweetations (10) Metrics

Journals

  1. Hu M, Rao A, Kejriwal M, Lerman K. Socioeconomic Correlates of Anti-Science Attitudes in the US. Future Internet 2021;13(6):160 View
  2. Lorenz-Spreen P, Oswald L, Lewandowsky S, Hertwig R. A systematic review of worldwide causal and correlational evidence on digital media and democracy. Nature Human Behaviour 2022;7(1):74 View
  3. Chen Y, Long J, Jun J, Kim S, Zain A, Piacentine C. Anti-intellectualism amid the COVID-19 pandemic: The discursive elements and sources of anti-Fauci tweets. Public Understanding of Science 2023;32(5):641 View
  4. Aygun I, Kaya B, Kaya M. Aspect Based Twitter Sentiment Analysis on Vaccination and Vaccine Types in COVID-19 Pandemic With Deep Learning. IEEE Journal of Biomedical and Health Informatics 2022;26(5):2360 View
  5. Zhu Y, Beam M, Ming Y, Egbert N, Smith T. A Social Cognitive Theory Approach to Understanding Parental Attitudes and Intentions to Vaccinate Children during the COVID-19 Pandemic. Vaccines 2022;10(11):1876 View
  6. Weinzierl M, Hopfer S, Harabagiu S. Scaling up the discovery of hesitancy profiles by identifying the framing of beliefs towards vaccine confidence in Twitter discourse. Journal of Behavioral Medicine 2023;46(1-2):253 View
  7. Darius P. Who polarizes Twitter? Ideological polarization, partisan groups and strategic networked campaigning on Twitter during the 2017 and 2021 German Federal elections 'Bundestagswahlen'. Social Network Analysis and Mining 2022;12(1) View
  8. Yuen V. Political attitudes and efficacy of health expert communication on the support for COVID-19 vaccination program: Findings from a survey in Hong Kong. Vaccine 2022;40(15):2282 View
  9. Block R, Burnham M, Kahn K, Peng R, Seeman J, Seto C. Perceived risk, political polarization, and the willingness to follow COVID-19 mitigation guidelines. Social Science & Medicine 2022;305:115091 View
  10. Rao A, Morstatter F, Lerman K. Partisan asymmetries in exposure to misinformation. Scientific Reports 2022;12(1) View
  11. Priniski J, Holyoak K, Delcea C. A darkening spring: How preexisting distrust shaped COVID-19 skepticism. PLOS ONE 2022;17(1):e0263191 View
  12. Jing F, Li Z, Qiao S, Zhang J, Olatosi B, Li X. Using geospatial social media data for infectious disease studies: a systematic review. International Journal of Digital Earth 2023;16(1):130 View
  13. Gori Maia A, Martinez J, Marteleto L, Rodrigues C, Sereno L. Can the Content of Social Networks Explain Epidemic Outbreaks?. Population Research and Policy Review 2023;42(1) View
  14. Mackey T, Baur C, Eysenbach G. Advancing Infodemiology in a Digital Intensive Era. JMIR Infodemiology 2022;2(1):e37115 View
  15. Botzer N, Weninger T. Entity graphs for exploring online discourse. Knowledge and Information Systems 2023;65(9):3591 View
  16. Lordan R, Devkota H. Turbulence at Twitter with leadership change: implications for health research and science communication. Exploration of Digital Health Technologies 2023:4 View
  17. Pierri F, Luceri L, Chen E, Ferrara E. How does Twitter account moderation work? Dynamics of account creation and suspension on Twitter during major geopolitical events. EPJ Data Science 2023;12(1) View
  18. Kristensen J, Henriksen F, Mayerhöffer E. Did COVID-19 Blur Partisan Boundaries? A Comparison of Partisan Affinity and Source Heterophily in Online Alternative News-Sharing Networks Before and During the COVID-19 Pandemic. Social Media + Society 2023;9(3) View
  19. Xia X, Zhang Y, Jiang W, Wu C. Staying Home, Tweeting Hope: Mixed Methods Study of Twitter Sentiment Geographical Index During US Stay-At-Home Orders. Journal of Medical Internet Research 2023;25:e45757 View
  20. Fiskvik J, Bjarkø A, Ihlen Ø. Trustworthiness Over Time on Twitter: Three Critical Periods for the Norwegian Health Authorities and Political Leadership During the COVID-19 Pandemic. Social Media + Society 2023;9(2):205630512311796 View
  21. Vilone D, Polizzi E, Vellucci P. Modeling opinion misperception and the emergence of silence in online social system. PLOS ONE 2024;19(1):e0296075 View
  22. Mayerhöffer E, Kristensen J, Ramsland T. Curators of digital counterpublics: Mapping alternative news environments in Sweden and Denmark. Nordicom Review 2024;45(s1):92 View
  23. Lerman K, Feldman D, He Z, Rao A. Affective polarization and dynamics of information spread in online networks. npj Complexity 2024;1(1) View
  24. Dickson Z, Yildirim T. The Effects of COVID-19 Infection on Opposition to COVID-19 Policies: Evidence from the U.S. Congress. Political Communication 2024:1 View

Books/Policy Documents

  1. Jarynowski A, Semenov A, Wójta-Kempa M, Belik V. Computational Data and Social Networks. View