Partisan differences in legislators’ discussion of vaccination on Twitter during the COVID-19 era: a natural language processing analysis (Preprint)

Author:

Engel-Rebitzer EdenORCID,Stokes Daniel CamargoORCID,Meisel Zachary FORCID,Purtle Jonathan,Doyle Rebecca,Buttenheim Alison

Abstract

BACKGROUND

The 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.

OBJECTIVE

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 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.

METHODS

We abstracted all vaccine-related tweets produced by state and federal legislators between 2/1/20 and 12/11/20. We used Latent Dirichlet allocation to define tweet topic and used descriptive statistics to describe differences by party in the use of topics and changes in political polarization over time.

RESULTS

We included 14,519 tweets generated by 1,463 state and 521 federal legislators. Republicans were more likely to use words (e.g., “record time”, “launched”, “innovation”) and topics (e.g., Operation Warp Speed success) that were focused on the successful development of a SARS-CoV-2 vaccine. Democrats used a broader range of words (e.g., “anti-vaxxers”, “flu”, “free”) and topics (e.g., vaccine prioritization, influenza, anti-vaxxers) that were more aligned with public health messaging related to the vaccine. Polarization increased over most of the study period.

CONCLUSIONS

Republican 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.

CLINICALTRIAL

Publisher

JMIR Publications Inc.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3