Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis

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 po...

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Main Authors: Eden Engel-Rebitzer, Daniel C Stokes, Zachary F Meisel, Jonathan Purtle, Rebecca Doyle, Alison M Buttenheim
Format: Article
Language:English
Published: JMIR Publications 2022-02-01
Series:JMIR Infodemiology
Online Access:https://infodemiology.jmir.org/2022/1/e32372
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author Eden Engel-Rebitzer
Daniel C Stokes
Zachary F Meisel
Jonathan Purtle
Rebecca Doyle
Alison M Buttenheim
author_facet Eden Engel-Rebitzer
Daniel C Stokes
Zachary F Meisel
Jonathan Purtle
Rebecca Doyle
Alison M Buttenheim
author_sort Eden Engel-Rebitzer
collection DOAJ
description 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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spelling doaj.art-c13805e5b879486886c72b97350393782023-08-28T20:50:16ZengJMIR PublicationsJMIR Infodemiology2564-18912022-02-0121e3237210.2196/32372Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing AnalysisEden Engel-Rebitzerhttps://orcid.org/0000-0002-5013-554XDaniel C Stokeshttps://orcid.org/0000-0002-9622-2761Zachary F Meiselhttps://orcid.org/0000-0001-8474-7993Jonathan Purtlehttps://orcid.org/0000-0001-6908-5944Rebecca Doylehttps://orcid.org/0000-0002-9354-540XAlison M Buttenheimhttps://orcid.org/0000-0003-2432-1637 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.https://infodemiology.jmir.org/2022/1/e32372
spellingShingle Eden Engel-Rebitzer
Daniel C Stokes
Zachary F Meisel
Jonathan Purtle
Rebecca Doyle
Alison M Buttenheim
Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis
JMIR Infodemiology
title Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis
title_full Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis
title_fullStr Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis
title_full_unstemmed Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis
title_short Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis
title_sort partisan differences in legislators discussion of vaccination on twitter during the covid 19 era natural language processing analysis
url https://infodemiology.jmir.org/2022/1/e32372
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