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推特揭示了撒哈拉以南非洲地区对疫苗担忧的时空变化。

Twitter reveals spatio-temporal variation in vaccine concerns in Sub-Saharan Africa.

作者信息

Jain Devansh, Rai Sunny, Mittal Juhi, Andy Anietie, Buttenheim Alison M, Guntuku Sharath Chandra

机构信息

Language Technologies Institute, School of Computer Science, Carnegie Mellon University.

Department of Computer and Information Science, University of Pennsylvania.

出版信息

medRxiv. 2025 Aug 24:2025.08.19.25334033. doi: 10.1101/2025.08.19.25334033.

Abstract

BACKGROUND

COVID-19 vaccine hesitancy, fueled by concerns about vaccine development, side effects, and misinformation on social media platforms like Twitter, resulted in lower vaccination rates in Sub-Saharan Africa.

METHODS

We collected, preprocessed, and geolocated 6,546,893 tweets related to COVID-19 vaccination from Sub-Saharan Africa. Using a vaccine misinformation classifier trained on RoBERTa embeddings, we identified 371,965 tweets in our dataset that included misinformation. We characterized the relationship between specific COVID-19 vaccine topics and the prevalence of misinformation, examined temporal variation in misinformation, and separately described the prevalence of misinformation in clusters defined by country-level socioeconomic and development metrics and by COVID-19 epidemiology.

RESULTS

Misinformation in Sub-Saharan Africa is associated with discussions about pharmaceutical company profits, global access to vaccines and disparity, and trust in scientific research regarding vaccines. The prevalence of misinformation topics varied widely across country clusters as defined by socioeconomic development and COVID-19 epidemiology metrics.

CONCLUSIONS

Social media data provides valuable insights about vaccine hesitancy and vaccine misinformation in Sub-Saharan Africa that can inform policy and programmatic interventions to support vaccine demand and vaccine promotion.

摘要

背景

对疫苗研发、副作用以及推特等社交媒体平台上错误信息的担忧加剧了撒哈拉以南非洲地区对新冠疫苗的犹豫态度,导致该地区疫苗接种率较低。

方法

我们收集、预处理并对来自撒哈拉以南非洲地区的6546893条与新冠疫苗接种相关的推文进行了地理定位。使用在RoBERTa嵌入上训练的疫苗错误信息分类器,我们在数据集中识别出371965条包含错误信息的推文。我们描述了特定新冠疫苗主题与错误信息流行率之间的关系,研究了错误信息的时间变化,并分别描述了按国家层面社会经济和发展指标以及新冠疫情流行病学定义的集群中错误信息的流行情况。

结果

撒哈拉以南非洲地区的错误信息与关于制药公司利润、全球疫苗获取与差距以及对疫苗科学研究的信任等讨论有关。根据社会经济发展和新冠疫情流行病学指标定义的国家集群中,错误信息主题的流行率差异很大。

结论

社交媒体数据为撒哈拉以南非洲地区的疫苗犹豫和疫苗错误信息提供了有价值的见解,可为支持疫苗需求和疫苗推广的政策及项目干预提供参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6004/12393616/9070cbdc2167/nihpp-2025.08.19.25334033v1-f0001.jpg

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