Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data.
Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data.
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DOI：
10.2196/26780
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发表时间：
2021-04-05
影响因子：
8.5
通讯作者：
Wahbeh A
中科院分区：
文献类型：
--
作者：
Al-Ramahi M;Elnoshokaty A;El-Gayar O;Nasralah T;Wahbeh A
尽管有科学证据支持戴口罩对遏制COVID-19传播的重要性，但戴口罩引发了一场重大辩论，尤其是在社交媒体上。本研究旨在调查与美国反对戴口罩的公共话语相关的主题。我们还研究了社交媒体上的反口罩话语与新冠肺炎病例数量之间的关系。我们在2020年1月1日至2020年10月27日期间，通过搜索反对戴口罩的标签，共收集了51，170条英文推文。我们使用机器学习技术来分析收集的数据。我们使用Pearson相关性分析两个时间序列，调查了反对戴口罩的推文数量与每日新冠病例数量之间的关系。结果和分析表明，社交媒体可以帮助识别与戴口罩有关的重要见解。主题挖掘的结果确定了用户关注的10个类别或主题，主要是（1）宪法权利和选择自由;（2）阴谋论，人口控制和大型制药公司;（3）假新闻，假数字和假流行病。这三类加起来，几乎占到了反对戴口罩的推文量的65%。反对戴口罩的推文数量与新报告的COVID-19病例之间的关系显示出强烈的相关性，其中负面推文数量的增加导致新病例数量增加了9天。这些发现表明挖掘社交媒体在理解有关公共卫生问题的公众话语（例如在COVID-19大流行期间戴口罩）方面的潜力。结果强调了社交媒体上的话语与对真实的事件的潜在影响之间的关系，例如改变大流行病的进程。建议政策制定者积极主动地解决公众的看法，并通过提高认识，揭穿消极情绪，并优先考虑对最流行的主题进行早期政策干预来塑造这种看法。
Despite scientific evidence supporting the importance of wearing masks to curtail the spread of COVID-19, wearing masks has stirred up a significant debate particularly on social media. This study aimed to investigate the topics associated with the public discourse against wearing masks in the United States. We also studied the relationship between the anti-mask discourse on social media and the number of new COVID-19 cases. We collected a total of 51,170 English tweets between January 1, 2020, and October 27, 2020, by searching for hashtags against wearing masks. We used machine learning techniques to analyze the data collected. We investigated the relationship between the volume of tweets against mask-wearing and the daily volume of new COVID-19 cases using a Pearson correlation analysis between the two-time series. The results and analysis showed that social media could help identify important insights related to wearing masks. The results of topic mining identified 10 categories or themes of user concerns dominated by (1) constitutional rights and freedom of choice; (2) conspiracy theory, population control, and big pharma; and (3) fake news, fake numbers, and fake pandemic. Altogether, these three categories represent almost 65% of the volume of tweets against wearing masks. The relationship between the volume of tweets against wearing masks and newly reported COVID-19 cases depicted a strong correlation wherein the rise in the volume of negative tweets led the rise in the number of new cases by 9 days. These findings demonstrated the potential of mining social media for understanding the public discourse about public health issues such as wearing masks during the COVID-19 pandemic. The results emphasized the relationship between the discourse on social media and the potential impact on real events such as changing the course of the pandemic. Policy makers are advised to proactively address public perception and work on shaping this perception through raising awareness, debunking negative sentiments, and prioritizing early policy intervention toward the most prevalent topics.
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DOI：
10.1073/pnas.2011674117
发表时间：
2020-09-08
影响因子：
11.1
作者：
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通讯作者：
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