Revealing the Global Linguistic and Geographical Disparities of Public Awareness to Covid-19 Outbreak through Social Media
Topics: Geographic Information Science and Systems
, Geographic Thought
,
Keywords: social media, Covid-19, public awareness, geographical disparities, linguistic disparities
Session Type: Virtual Paper Abstract
Day: Sunday
Session Start / End Time: 2/27/2022 03:40 PM (Eastern Time (US & Canada)) - 2/27/2022 05:00 PM (Eastern Time (US & Canada))
Room: Virtual 31
Authors:
Binbin Lin, Texas A&M University
Lei Zou, Texas A&M University
Heng Cai, Texas A&M University
Bing Zhou, Texas A&M University
Mingzheng Yang, Texas A&M University
Debayan Mandal, Texas A&M University
Joynal Abedin, Texas A&M University
,
,
,
Abstract
The Covid-19 pandemic has profoundly impacted human societies worldwide and presented an unprecedented challenge to public health. However, residents in different countries showed diverse levels of awareness to Covid-19 during the outbreak and suffered from uneven health impacts. This study analyzed the global Twitter data from January 1st to June 30th, 2020. We seek to answer two research questions. First, what are the linguistic and geographical disparities of public awareness in the Covid-19 outbreak period reflected on social media? Second, can the changing pandemic awareness predict the Covid-19 outbreak? We established a Twitter data mining framework calculating the Ratio index to quantify and track the public awareness of Covid-19 by different languages and at multiple spatial and temporal scales. The lag correlations between Covid-19 awareness and health impacts were examined at both global and country levels. Results confirmed the existence of linguistic and geographical disparities of public awareness in different countries. Users presenting the highest awareness toward the Covid-19 outbreak were mainly those tweeting in regional or official languages of India and Bangladesh. Asian countries showed more significant disparities in public awareness than European countries, and public awareness in the eastern part of Europe was higher than in central Europe. Finally, the Ratio index could accurately predict global mortality rate and case fatality ratio with 21-30 and 35-42 leading days. The Ratio index performed the best in predicting mortality rate at the country level, and the average leading days were 17.
Revealing the Global Linguistic and Geographical Disparities of Public Awareness to Covid-19 Outbreak through Social Media
Category
Virtual Paper Abstract
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