Department of Applied Health Science, School of Public Health, Indiana University, Bloomington, IN, United States.
Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, United States.
J Med Internet Res. 2020 Dec 14;22(12):e21418. doi: 10.2196/21418.
The COVID-19 pandemic led to unprecedented mitigation efforts that disrupted the daily lives of millions. Beyond the general health repercussions of the pandemic itself, these measures also present a challenge to the world's mental health and health care systems. Considering that traditional survey methods are time-consuming and expensive, we need timely and proactive data sources to respond to the rapidly evolving effects of health policy on our population's mental health. Many people in the United States now use social media platforms such as Twitter to express the most minute details of their daily lives and social relations. This behavior is expected to increase during the COVID-19 pandemic, rendering social media data a rich field to understand personal well-being.
This study aims to answer three research questions: (1) What themes emerge from a corpus of US tweets about COVID-19? (2) To what extent did social media use increase during the onset of the COVID-19 pandemic? and (3) Does sentiment change in response to the COVID-19 pandemic?
We analyzed 86,581,237 public domain English language US tweets collected from an open-access public repository in three steps. First, we characterized the evolution of hashtags over time using latent Dirichlet allocation (LDA) topic modeling. Second, we increased the granularity of this analysis by downloading Twitter timelines of a large cohort of individuals (n=354,738) in 20 major US cities to assess changes in social media use. Finally, using this timeline data, we examined collective shifts in public mood in relation to evolving pandemic news cycles by analyzing the average daily sentiment of all timeline tweets with the Valence Aware Dictionary and Sentiment Reasoner (VADER) tool.
LDA topics generated in the early months of the data set corresponded to major COVID-19-specific events. However, as state and municipal governments began issuing stay-at-home orders, latent themes shifted toward US-related lifestyle changes rather than global pandemic-related events. Social media volume also increased significantly, peaking during stay-at-home mandates. Finally, VADER sentiment analysis scores of user timelines were initially high and stable but decreased significantly, and continuously, by late March.
Our findings underscore the negative effects of the pandemic on overall population sentiment. Increased use rates suggest that, for some, social media may be a coping mechanism to combat feelings of isolation related to long-term social distancing. However, in light of the documented negative effect of heavy social media use on mental health, social media may further exacerbate negative feelings in the long-term for many individuals. Thus, considering the overburdened US mental health care structure, these findings have important implications for ongoing mitigation efforts.
COVID-19 大流行导致了前所未有的缓解措施，扰乱了数百万人的日常生活。除了大流行本身对一般健康的影响外，这些措施也对世界的精神健康和医疗保健系统构成了挑战。考虑到传统的调查方法既费时又昂贵，我们需要及时和积极主动的数据源来应对卫生政策对我们人口精神健康的迅速变化的影响。现在，许多美国人使用 Twitter 等社交媒体平台来表达日常生活和社会关系中最细微的细节。预计在 COVID-19 大流行期间，这种行为会增加，使社交媒体数据成为了解个人幸福感的丰富领域。
本研究旨在回答三个研究问题：（1）关于 COVID-19 的美国推特语料库中出现了哪些主题？（2）在 COVID-19 大流行开始时，社交媒体的使用增加了多少？以及（3）情绪是否会因 COVID-19 大流行而改变？
我们分三步分析了从开放获取公共存储库中收集的 8658.123 万条公共领域英语美国推特数据。首先，我们使用潜在狄利克雷分配 (LDA)主题建模来描述随时间演变的标签的演变。其次，我们通过下载 20 个美国主要城市的 354738 名个人的推特时间线，增加了这一分析的粒度，以评估社交媒体使用的变化。最后，使用这些时间线数据，我们通过分析所有时间线推特的平均日常情绪，使用 Valence Aware Dictionary 和 Sentiment Reasoner (VADER) 工具来研究与不断演变的大流行病新闻周期相关的公众情绪的集体转变。
在数据集的早期阶段生成的 LDA 主题与 COVID-19 特定事件相对应。然而，随着州和市政府开始发布就地避难令，潜在的主题转向了与美国相关的生活方式改变，而不是与全球大流行相关的事件。社交媒体的使用量也显著增加，在就地避难令期间达到峰值。最后，用户时间线的 VADER 情绪分析分数最初较高且稳定，但到 3 月底后显著且持续下降。
我们的研究结果强调了大流行对总体人口情绪的负面影响。使用率的增加表明，对于某些人来说，社交媒体可能是一种应对长期社交隔离相关孤立感的机制。然而，鉴于大量使用社交媒体对心理健康的负面影响，从长期来看，社交媒体可能会进一步加剧许多人的负面情绪。因此，考虑到美国精神卫生保健结构负担过重，这些发现对正在进行的缓解努力具有重要意义。
