Cited by 100Vaccine Coverage and HesitancyMisinformation and Its ImpactsCommunication and COVID-19 Impact

Social media behavior is associated with vaccine hesitancy

Open access
Rathje, Steve, He, James K, Roozenbeek, Jon, Van Bavel, Jay J, van der Linden, Sander·2022·PNAS Nexus

Abstract

Understanding how vaccine hesitancy relates to online behavior is crucial for addressing current and future disease outbreaks. We combined survey data measuring attitudes toward the COVID-19 vaccine with Twitter data in two studies (N1 = 464 Twitter users, N2 = 1,600 Twitter users) with preregistered hypotheses to examine how real-world social media behavior is associated with vaccine hesitancy in the United States (US) and the United Kingdom (UK). In Study 1, we found that following the accounts of US Republican politicians or hyper-partisan/low-quality news sites were associated with lower confidence in the COVID-19 vaccine—even when controlling for key demographics such as self-reported political ideology and education. US right-wing influencers (e.g. Candace Owens, Tucker Carlson) had followers with the lowest confidence in the vaccine. Network analysis revealed that participants who were low and high in vaccine confidence separated into two distinct communities (or “echo chambers”), and centrality in the more right-wing community was associated with vaccine hesitancy in the US, but not in the UK. In Study 2, we found that one's likelihood of not getting the vaccine was associated with retweeting and favoriting low-quality news websites on Twitter. Altogether, we show that vaccine hesitancy is associated with following, sharing, and interacting with low-quality information online, as well as centrality within a conservative-leaning online community in the US. These results illustrate the potential challenges of encouraging vaccine uptake in a polarized social media environment.

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  • Pro-vaccine individuals in the United States tended to follow liberal politicians on Twitter, whereas anti-vaccine individuals were more likely to follow conservative politicians and influencers.

    “Pro-vaccine individuals in the United States tended to follow liberal politicians on Twitter (such as Kamala Harris and Hillary Clinton), whereas anti-vaccine individuals were more likely to follow conservative politicians and influencers (such as Candace Owens or Tucker Carlson).”

    From Social Media and Morality. (2024) · cites this paper as Rathje et al. 2022

  • Americans with anti-vaccine and pro-vaccine attitudes clustered into distinct echo chambers on Twitter.

    “Americans with anti-vaccine and pro-vaccine attitudes clustered into distinct echo chambers on Twitter (Rathje et al. 2022).”

    From Social Media and Morality. (2024) · cites this paper as Rathje et al. 2022

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Research works printed but not linked: 27

  1. [4]Johnson NF, et al. 2020. The online competition between pro-and anti-vaccination views. Nature. 582: 230– 233. 32499650
  2. [9]Romer D, Jamieson KH. 2020. Conspiracy theories as barriers to controlling the spread of COVID-19 in the US. Soc Sci Med. 263: 113356. 32967786 PMC7502362
  3. [10]Pierri M. et al. 2022. Online misinformation is linked to early COVID-19 vaccination hesitancy and refusal. Scientific Reports. 12(5966): 1– 7. 35474313 PMC9043199
  4. [11]Roozenbeek J, et al. 2020. Susceptibility to misinformation about COVID-19 around the world. R Soc Open Sci. 7: 201199. 33204475 PMC7657933
  5. [13]Lazer D, et al. 2021. The COVID States Project #57: social media news consumption and COVID-19 vaccination rates. 10.31219/osf.io/uvqbs. · DOI · Paper page
  6. [14]Fridman A, Gershon R, Gneezy A. 2021. COVID-19 and vaccine hesitancy: a longitudinal study. PLoS One. 16: e0250123. 33861765 PMC8051771
  7. [16]Gollwitzer A, et al. 2020. Partisan differences in physical distancing are linked to health outcomes during the COVID-19 pandemic. Nat Hum Behav. 4: 1– 12. 33139897
  8. [17]Pink S, Chu J, Druckman J, Rand D, Willer R. 2021. Elite party cues increase vaccination intentions among republicans. Proc Natl Acad Sci. 118: e2106559118. 34312254 PMC8364165
  9. [18]Pavlovic. et al. 2022. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning. PNAS Nexus. 1(3): 1– 15. PMC9381137 35990802
  10. [19]Freeman D, et al. 2020. COVID-19 vaccine hesitancy in the UK: the Oxford coronavirus explanations, attitudes, and narratives survey (Oceans) II. Psychol Med. 1– 15. PMC7804077 33305716
  11. [20]Van Bavel JJ, et al. 2022. National identity predicts public health support during a global pandemic. Nat Commun. 13: 1– 14. 35082277 PMC8792004
  12. [21]Pennycook G, McPhetres J, Bago B, Rand DG. 2021. Beliefs about COVID-19 in Canada, the United Kingdom, and the United States: a novel test of political polarization and motivated reasoning. Personal Soc Psychol Bull. 48: (5): 750– 765. PMC9066691 34180276
  13. [22]Cohen GL. 2003. Party over policy: the dominating impact of group influence on political beliefs. J Pers Soc Psychol. 85: 808. 14599246
  14. [23]Barberá P, Jost JT, Nagler J, Tucker JA, Bonneau R. 2015. Tweeting from left to right: is online political communication more than an echo chamber?. Psychol Sci. 26: 1531– 1542. 26297377
  15. [27]Brown JR, Enos RD. 2021. The measurement of partisan sorting for 180 million voters. Nat Hum Behav. 5: 1– 11. 33686203
  16. [30]Mosleh M, Pennycook G, Arechar AA, Rand DG. 2021. Cognitive reflection correlates with behavior on Twitter. Nat Commun. 12: 1– 10. 33568667 PMC7875970
  17. [33]Guess A, Nagler J, Tucker J. 2019. Less than you think: prevalence and predictors of fake news dissemination on Facebook. Sci Adv. 5: eaau4586. 30662946 PMC6326755
  18. [35]Bhadani S, et al. 2022. Political audience diversity and news reliability in algorithmic ranking. Nat Hum Behav. 6: 1– 11. 35115677
  19. [36]Raghavan UN, Albert R, Kumara S. 2007. Near linear time algorithm to detect community structures in large-scale networks. Phys Rev E. 76: 036106. 17930305
  20. [39]Brandes U, et al. 2007. On modularity clustering. IEEE Trans Knowl Data Eng. 20: 172– 188.
  21. [40]Newman ME. 2003. Mixing patterns in networks. Phys Rev E. 67: 026126. 12636767
  22. [45]Aral S, Muchnik L, Sundararajan A. 2009. Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks. Proc Natl Acad Sci. 106: 21544– 21549. 20007780 PMC2799846
  23. [54]Flores A, et al. 2022. Politicians polarize and experts depolarize public support for COVID-19 management policies across countries. Proc Natl Acad Sci. 119: e2117543119. 35042779 PMC8784107
  24. [55]Larsen B, et al. 2022. Using Donald Trump's COVID-19 vaccine endorsement to give public health a shot in the arm: a large-scale Ad experiment. National Bureau of Economic Research, doi: 10.3386/w29896. · DOI
  25. [59]Chu J, Pink SL, Willer R. 2021. Religious identity cues increase vaccination intentions and trust in medical experts among American Christians. Proc Natl Acad Sci. 118: e210648111. PMC8670469 34795017
  26. [60]Guess AM, et al. 2020. A digital media literacy intervention increases discernment between mainstream and false news in the United States and India. Proc Natl Acad Sci. 117: 15536– 15545. 32571950 PMC7355018
  27. [64]Maertens R, et al. 2021. The misinformation susceptibility test (MIST): a psychometrically validated measure of news veracity discernment. PsyArXiv. 10.31234/osf.io/gk68h. PMC10991074 37382812 · DOI

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Authors
Rathje, S., He, J. K., Roozenbeek, J., Van Bavel, J. J., & van der Linden, S.
Affiliations
  • New York University (US)
  • University of Cambridge (GB)
  • Department of Psychology & Center for Neural Science, New York University , New York, NY 10003 , USA
Corresponding author
Rathje, Steve
Venue
PNAS Nexus
Published
2022-09-01
Volume
1
Issue
4
Pages
pgac207-pgac207
ISSN
2752-6542 (ISSN-L)
OpenAlex
W4297453923
Cited by
100
References
16
Citations by year
2026: 14 · 2025: 27 · 2024: 34 · 2023: 23 · 2022: 1 · 2021: 1
FWCI
16.51
Type
journal article
Language
en
Open access
Locations
  • PNAS Nexus (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • Apollo (cc-by)
Funders
Economic and Social Research Council (ES/V011960/1)
Topics
  • Social Sciences › Health › Vaccine Coverage and Hesitancy
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Social Sciences › Communication › Communication and COVID-19 Impact
Keywords
vaccine hesitancy, social media behavior, Twitter, political polarization, echo chambers, retweets, political ideology, vaccine uptake, network centrality

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