ArticleJMIR infodemiology
Partisan Differences in Legislators' Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis.
Article in JMIR infodemiology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Drivers of health polarization during the COVID-19 pandemic: A systematic review.Science advances · 2025Pooled it
- SciComm Optimizer for Policy Engagement: a randomized controlled trial of the SCOPE model on state legislators' research use in public discourse.Implementation science : IS · 2023Trial
- Firearm Violence and Health in Policymaker Discourse: Mixed Methods Social Media Analysis.JMIR formative research · 2025Article
- Using Machine Learning Technology (Early Artificial Intelligence-Supported Response With Social Listening Platform) to Enhance Digital Social Understanding for the COVID-19 Infodemic: Development and Implementation Study.JMIR infodemiology · 2023Article
- Mistrust in public health institutions is a stronger predictor of vaccine hesitancy and uptake than Trust in Trump.Social science & medicine (1982) · 2022Article
- Social media and attitudes towards a COVID-19 vaccination: A systematic review of the literature.EClinicalMedicine · 2022Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundThe COVID-19 era has been characterized by the politicization of health-related topics. This is especially concerning given evidence that politicized discussion of vaccination may contribute to vaccine hesitancy. No research, however, has examined the content and politicization of legislator communication with the public about vaccination during the COVID-19 era.
objectiveThe aim of this study was to examine vaccine-related tweets produced by state and federal legislators during the COVID-19 era to (1) describe the content of vaccine-related tweets; (2) examine the differences in vaccine-related tweet content between Democrats and Republicans; and (3) quantify (and describe trends over time in) partisan differences in vaccine-related communication.
methodsWe abstracted all vaccine-related tweets produced by state and federal legislators between February 01, 2020, and December 11, 2020. We used latent Dirichlet allocation to define the tweet topics and used descriptive statistics to describe differences by party in the use of topics and changes in political polarization over time.
resultsWe included 14,519 tweets generated by 1463 state legislators and 521 federal legislators. Republicans were more likely to use words (eg, "record time," "launched," and "innovation") and topics (eg, Operation Warp Speed success) that were focused on the successful development of a SARS-CoV-2 vaccine. Democrats used a broader range of words (eg, "anti-vaxxers," "flu," and "free") and topics (eg, vaccine prioritization, influenza, and antivaxxers) that were more aligned with public health messaging related to the vaccine. Polarization increased over most of the study period.
conclusionsRepublican and Democratic legislators used different language in their Twitter conversations about vaccination during the COVID-19 era, leading to increased political polarization of vaccine-related tweets. These communication patterns have the potential to contribute to vaccine hesitancy.
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