Texas A&M University-San Antonio, San Antonio, TX, United States.
Northern Michigan University, Marquette, MI, United States.
JMIR Public Health Surveill. 2021 Apr 5;7(4):e26780. doi: 10.2196/26780.
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.
尽管有科学证据表明佩戴口罩对于遏制 COVID-19 传播至关重要，但佩戴口罩已引发了一场激烈的辩论，尤其是在社交媒体上。
本研究旨在调查与美国公众反对戴口罩相关的话题。我们还研究了社交媒体上的反口罩言论与新的 COVID-19 病例数量之间的关系。
我们通过搜索反对戴口罩的标签，共收集了 2020 年 1 月 1 日至 10 月 27 日期间的 51170 条英语推文。我们使用机器学习技术来分析收集的数据。我们通过对两个时间序列进行皮尔逊相关分析，研究了反戴口罩推文量与每日新增 COVID-19 病例量之间的关系。
结果和分析表明，社交媒体可以帮助识别与戴口罩相关的重要见解。主题挖掘的结果确定了用户关注的 10 个类别或主题，其中包括（1）宪法权利和自由选择；（2）阴谋论、人口控制和大制药公司；以及（3）假新闻、假数据和假大流行。这三个类别总共占反戴口罩推文量的近 65%。反戴口罩推文量与新报告的 COVID-19 病例之间的关系显示出很强的相关性，即负面推文量的增加导致新病例数增加了 9 天。
这些发现表明，挖掘社交媒体对于理解 COVID-19 大流行期间佩戴口罩等公共卫生问题的公众讨论具有潜力。研究结果强调了社交媒体上的言论与改变疫情进程等实际事件之间的潜在影响。建议政策制定者积极解决公众的看法，并通过提高认识、驳斥负面情绪以及优先处理最普遍的话题来塑造这种看法。
