Objective

The potential ability for weather to affect SARS-CoV-2 transmission has been an area of controversial discussion during the COVID-19 pandemic. Individuals’ perceptions of the impact of weather can inform their adherence to public health guidelines; however, there is no measure of their perceptions. We quantified Twitter users’ perceptions of the effect of weather and analyzed how they evolved with respect to real-world events and time.

Materials and Methods

We collected 166,005 English tweets posted between January 23 and June 22, 2020 and employed machine learning/natural language processing techniques to filter for relevant tweets, classify them by the type of effect they claimed, and identify topics of discussion.

Results

We identified 28,555 relevant tweets and estimate that 40.4 % indicate uncertainty about weather’s impact, 33.5 % indicate no effect, and 26.1 % indicate some effect. We tracked changes in these proportions over time. Topic modeling revealed major latent areas of discussion.

Discussion

There is no consensus among the public for weather’s potential impact. Earlier months were characterized by tweets that were uncertain of weather’s effect or claimed no effect; later, the portion of tweets claiming some effect of weather increased. Tweets claiming no effect of weather comprised the largest class by June. Major topics of discussion included comparisons to influenza’s seasonality, President Trump’s comments on weather’s effect, and social distancing.

Conclusion

We exhibit a research approach that is effective in measuring population perceptions and identifying misconceptions, which can inform public health communications.

中文翻译：

---

天气是否会帮助我们应对 COVID-19 大流行：使用机器学习来衡量 Twitter 用户的看法

客观的

在 COVID-19 大流行期间，天气影响 SARS-CoV-2 传播的潜在能力一直是一个有争议的讨论领域。个人对天气影响的看法可以帮助他们遵守公共卫生准则；然而，无法衡量他们的看法。我们量化了 Twitter 用户对天气影响的看法，并分析了他们相对于现实世界事件和时间的演变。

材料和方法

我们收集了 2020 年 1 月 23 日至 6 月 22 日期间发布的 166,005 条英文推文，并采用机器学习/自然语言处理技术来过滤相关推文，根据其声称的效果类型对它们进行分类，并识别讨论主题。

结果

我们识别了 28,555 条相关推文，并估计 40.4% 表示天气影响的不确定性，33.5% 表示没有影响，26.1% 表示有影响。我们跟踪了这些比例随时间的变化。主题建模揭示了主要的潜在讨论领域。

讨论

公众对于天气的潜在影响尚未达成共识。前几个月的特点是推文不确定天气的影响或声称没有影响；后来，声称受到天气影响的推文比例有所增加。截至 6 月，声称不受天气影响的推文数量最多。主要讨论话题包括与流感季节性的比较、特朗普总统对天气影响的评论以及社交距离。

结论

我们展示了一种研究方法，可以有效衡量人们的看法并识别误解，从而为公共卫生沟通提供信息。