Human behavior in the time of COVID-19: Learning from big data

被引:4
作者
Lyu, Hanjia [1 ]
Imtiaz, Arsal [1 ]
Zhao, Yufei [1 ]
Luo, Jiebo [1 ]
机构
[1] Univ Rochester, Dept Comp Sci, Rochester, NY 14627 USA
来源
FRONTIERS IN BIG DATA | 2023年 / 6卷
关键词
big data; human behavior; COVID-19; machine learning; epidemiology-descriptive; SENSITIVITY-ANALYSIS; FACE MASKS; TWITTER; MODEL; SURVEILLANCE; EMOTIONS; OUTBREAK; QUALITY; SPEECH; SYSTEM;
D O I
10.3389/fdata.2023.1099182
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
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页数:16
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