Since the World Health Organization (WHO) characterized COVID-19 as a pandemic in March 2020, there have been over 600 million confirmed cases of COVID-19 and more than six million deaths as of October 2022. The relationship between the COVID-19 pandemic and human behavior is complicated. On one hand, human behavior is found to shape the spread of the disease. On the other hand, the pandemic has impacted and even changed human behavior in almost every aspect. To provide a holistic understanding of the complex interplay between human behavior and the COVID-19 pandemic, researchers have been employing big data techniques such as natural language processing, computer vision, audio signal processing, frequent pattern mining, and machine learning. In this study, we present an overview of the existing studies on using big data techniques to study human behavior in the time of the COVID-19 pandemic. In particular, we categorize these studies into three groups - using big data to measure, model, and leverage human behavior, respectively. The related tasks, data, and methods are summarized accordingly. To provide more insights into how to fight the COVID-19 pandemic and future global catastrophes, we further discuss challenges and potential opportunities.
翻译:自世界卫生组织于2020年3月宣布COVID-19为大流行病以来,截至2022年10月已确认超过6亿例COVID-19确诊病例和600万余例死亡病例。COVID-19疫情与人类行为之间的关系十分复杂。一方面,人类行为被发现影响着疾病的传播。另一方面,疫情影响并改变了几乎所有方面的人类行为。为了提供对人类行为与COVID-19疫情之间复杂相互作用的全面理解,研究人员一直在采用自然语言处理、计算机视觉、音频信号处理、频繁模式挖掘和机器学习等大数据技术。在本研究中,我们概述了现有的使用大数据技术研究COVID-19疫情期间人类行为的研究。特别是,我们根据大数据测量、建模和利用人类行为将这些研究分类到三类,并相应地总结了相关任务、数据和方法。为了提供更多有关如何应对COVID-19疫情和未来全球灾难的洞察,我们进一步讨论了挑战和潜在机会。