Relationship between Google Trend and Daily Trend of New COVID-19 cases in the United States

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  • September 16, 2021
Creator
  • Guolin Wang
Abstract
  • This study is a statistical analysis examining the relationship between Google Trend and Daily Trend of the number of new COVID-19 cases in the United States using single term versus selecting 5 terms per day and taking time-lag into account. Google Trend was used to measure the interest of users in search terms over time during the pandemic of COVID-19. To make up for the lack of open datasets of search queries, tweets filtered by “COVID-19” related hashtags were used to generate top-5 terms per day according to term frequency on a 7-day moving average. Spearman correlation analysis was applied to examine the correlations between the two trends and examine the impact of time-lag. The results showed high correlation between the two trends by selecting 5 terms per day. Besides, taking time-lag into account improved the correlation between the difference of search interest and the number of new COVID-19 cases. The results indicate that it is important to account for the fact that covid-related language may change over time and time-lag should be considered as an important factor when conducting trend analysis. This study demonstrates the possibility of using Google Trend to predict future case trend of COVID-19 in areas with a large population of Web search users.
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  • In Copyright
Advisor
  • Jaime Arguello
Degree
  • Master of Science in Information Science
Graduation year
  • 2021
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