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公众对 COVID-19 疫苗强制接种令的看法:基于机器学习的美国推特分析。

Public Opinions toward COVID-19 Vaccine Mandates: A Machine Learning-based Analysis of U.S. Tweets.

机构信息

University of California, Irvine, Irvine, CA, USA.

Hong Kong University of Science and Technology, Hong Kong SAR, China.

出版信息

AMIA Annu Symp Proc. 2023 Apr 29;2022:502-511. eCollection 2022.

Abstract

While it has been scientifically proven that COVID-19 vaccine is a safe and effective measure to reduce the severity of infection and curbing the spread of the SARS-CoV-2 virus, skepticism remains widespread, and in many countries vaccine mandates have been met with strong opposition. In this study, we applied machine learning-based analyses of the U.S.-based tweets covering the periods leading toward and after the Biden Administration's announcement of federal vaccine mandates, supplemented by a qualitative content analysis of a random sample of relevant tweets. The objective was to examine the beliefs held among twitter users toward vaccine mandates, as well as the evidence that they used to support their positions. The results show that while approximately 30% of the twitter users included in the dataset supported the measure, more users expressed differing opinions. Concerns raised included questioning on the political motive, infringement of personal liberties, and ineffectiveness in preventing infection.

摘要

虽然科学已经证明 COVID-19 疫苗是一种安全有效的措施,可以降低感染的严重程度并遏制 SARS-CoV-2 病毒的传播,但仍存在广泛的怀疑,而且在许多国家,疫苗授权遭到了强烈反对。在这项研究中,我们应用基于机器学习的分析方法,对美国在拜登政府宣布联邦疫苗授权前后的推文进行了分析,并对相关推文的随机样本进行了定性内容分析。目的是研究推特用户对疫苗授权的看法,以及他们用来支持自己立场的证据。结果表明,虽然在纳入研究的数据集的推特用户中,约有 30%的人支持这一措施,但也有更多的用户表达了不同的意见。提出的担忧包括对政治动机的质疑、侵犯个人自由以及在防止感染方面的无效性。

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The anti-vaccination infodemic on social media: A behavioral analysis.社交媒体上的反疫苗信息疫情:行为分析。
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