Revealing the Long-Term Global Awareness of Covid-19 and its Effects on Public Health through the Lens of Social Media

Authors: Binbin Lin*, Texas A&M University, Lei Zou, Texas A&M University, Mingzheng Yang, Texas A&M University, Bing Zhou, Texas A&M University
Topics: Geographic Information Science and Systems, Spatial Analysis & Modeling, Hazards, Risks, and Disasters
Keywords: Covid-19, social media, awareness, spatial-temporal analysis, health impacts
Session Type: Virtual Paper
Day: 4/7/2021
Start / End Time: 4:40 PM / 5:55 PM
Room: Virtual 7
Presentation File: No File Uploaded


Since December 2019, Covid-19 has infected nearly forty million people and caused one million fatalities. However, residents in different countries showed various awareness levels of this outbreak and suffered unequal health impacts. As the case number continues proliferating, investigating the disparities of public awareness towards the coronavirus and examining their effects on the infections and fatalities in different countries are essential to prevent the spread of the disease and recover from the pandemic. During Covid-19, numerous users followed news of the pandemic on social media, providing an innovative platform to track real-time public awareness. This research analyzed the global Twitter data from January to June 2020 to reveal the long-term spatial-temporal trends of public awareness towards Covid-19 and examine its relationship with the spread of this pandemic. The objectives are three-fold: (1) to develop a social media mining framework of capturing near real-time situation awareness; (2) to leverage Twitter data to reveal disparities of global awareness towards Covid-19; and (3) to examine the effects of public awareness on public health. First, Twitter data were preprocessed to derive the awareness index. Second, the Twitter-derived awareness index and public health impacts of Covid-19 were calculated and visualized at different spatial-temporal scales. Third, we analyzed the correlation between the Awareness Index and the spread of Covid-19 in selected countries. The developed framework could be applied to monitor public awareness of hazardous events. The analysis results could shed light on strategies to mitigate the public health impacts of future pandemics.

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