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SRP. 2020; 11(9): 431-438


The Correlation of Google Trends as an Alternative Information Source in the Early Stages of COVID-19 Outbreak in Indonesia

Elly Usman, Ricvan Dana Nindrea.




Abstract

This study conducted correlation of google trends as an alternative information source in the early stages of COVID-19 outbreak in Indonesia. Time series approach was used in this study. We sought to compare the official COVID-19 report in Indonesia accessible on a daily basis as well as information searches in Google Trends regarding COVID-19. Data analysis was performed using moving average in Minitab version 18.0. Correlation were calculated using pearson correlation and Time lag. R value ≥ 0.7 (p ≤ 0.05) was defined strong correlation. Moving average analysis showed a linear time series pattern between COVID-19 search trends and the official COVID-19 report. Pearson correlation analysis indicated strong correlation with R value ranging from 0.870-0.927 (p ≤ 0,05) among the four keywords used in Google trends with the official report of COVID-19 in Indonesia. Time lag correlation inference COVID-19 search trends data could possibly be utilized for an early identification of public reaction against the increasing cases of COVID-19. In the early stages of COVID-19 outbreak found the correlations and similarity of linear time series patterns are shown between COVID-19 search trends and the official COVID-19 report. Public behavior in information seeking is useful in early identification of disease outbreaks in Indonesia.

Key words: COVID-19; Digital Epidemiology; Google Trends; Indonesia; Information Seeking






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