The impact of the pandemic declaration on public awareness and behavior: Focusing on COVID-19 google searches

https://doi.org/10.1016/j.techfore.2021.120592Get rights and content
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Highlights

  • WHO pandemic declaration had a significant impact on public awareness and behavior.

  • Pandemic declaration increased Google searches related to COVID-19 by more than 20%.

  • Increased public awareness also raised interest in the COVID-19 test.

  • Increased public awareness eventually helped to find new cases of COVID-19 early.

  • Google search data can be used for decision making such as pandemic declaration.

Abstract

The unprecedented outbreaks of epidemics such as the coronavirus has caused major socio-economic changes. To analyze public risk awareness and behavior in response to the outbreak of epidemic diseases, this study focuses on RSV (Relative Search Volume) provided by Google Trends. This study uses the social big data provided by Google RSV to investigate how the WHO's pandemic declaration affected public awareness and behavior. 37 OECD countries were analyzed and clustered according to the degree of reaction to the declaration, and the United States, France and Germany were selected for comparative study. The results of this study statistically confirmed that the pandemic declaration increased public awareness and had the effect of increasing searches for information on COVID-19 by more than 20%. In addition, this rapid rise in RSV also reflected interest in the COVID-19 test and had the effect of inducing individuals to be tested, which helped identify new cases. The significance of this study is that it provided the theoretical foundation for using RSV and its implications to understand and strategically utilize public awareness and behavior in situations where the WHO and governments must launch policies in response to the outbreak of new infectious diseases such as COVID-19.

Keywords

Coronavirus
COVID-19
Public awareness
Google Trends
Relative search volume
Pandemic declaration

Cited by (0)

Seung-Pyo Jun is a principal researcher of Data Analysis Platform Center at the Korea Institute of Science and Technology Information (KISTI). Also, he is a professor of Science and Technology Management Policy in University of Science & Technology (UST). He received his Ph.D. from the Science and Technology Studies Program at Korea University. His area of interest includes the demand forecasting, emerging technology detecting and new technology adoption analysis. Recently he is focusing on the science technology and SMES supporting policy using data intelligence.

Hyoung Sun Yoo is a principal researcher at the Korea Institute of Science and Technology Information (KISTI). Also, he is an assistant professor of Science and Technology Management Policy in University of Science & Technology (UST). His area of interest includes demand forecasting, science and technology policy, complex network, and agent-based modeling.

Jae-Seong Lee is a Ph.D. student in Science and Technology Management Policy at University of Science & Technology (UST). He is also a student researcher at the Data Analysis Platform Center in Korea Institute of Science and Technology Information (KISTI). His areas of interest include National Innovation Systems (NIS), R&D project management, R&D collaboration management, innovation policies for SMEs, and Decision-making Support Systems (DSS) based on machine learning and Artificial Intelligence.