Suppr超能文献

新冠疫情期间伊维菌素推文的政治化现象

The Politicization of Ivermectin Tweets During the COVID-19 Pandemic.

作者信息

Diaz Marlon I, Hanna John J, Hughes Amy E, Lehmann Christoph U, Medford Richard J

机构信息

Clinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, Texas.

Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.

出版信息

Open Forum Infect Dis. 2022 Jun 6;9(7):ofac263. doi: 10.1093/ofid/ofac263. eCollection 2022 Jul.

Abstract

BACKGROUND

We explore the ivermectin discourse and sentiment in the United States with a special focus on political leaning through the social media blogging site Twitter.

METHODS

We used sentiment analysis and topic modeling to geospatially explore ivermectin Twitter discourse in the United States and compared it to the political leaning of a state based on the 2020 presidential election.

RESULTS

All modeled topics were associated with a negative sentiment. Tweets originating from democratic leaning states were more likely to be negative.

CONCLUSIONS

Real-time analysis of social media content can identify public health concerns and guide timely public health interventions tackling disinformation.

摘要

背景

我们通过社交媒体博客网站推特,特别关注政治倾向,探讨美国的伊维菌素相关言论和情绪。

方法

我们使用情感分析和主题建模,对美国伊维菌素相关推特言论进行地理空间探索,并将其与基于2020年总统选举的州政治倾向进行比较。

结果

所有建模主题都与负面情绪相关。来自倾向民主党的州的推文更有可能是负面的。

结论

对社交媒体内容的实时分析可以识别公共卫生问题,并指导及时应对虚假信息的公共卫生干预措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8d/9290534/8b7ceb9ea0c3/ofac263f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验