Revealing the linguistic and geographical disparities of public awareness to Covid-19 outbreak through social media. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Lin, Binbin; Zou, Lei; Duffield, Nick; Mostafavi, Ali; Cai, Heng; Zhou, Bing; Tao, Jian; Yang, Mingzheng; Mandal, Debayan; Abedin, Joynal
• Is Part Of: International journal of digital earth. Volume 15:Issue 1(2022)
• Page Start: 868
• Page End: 889
• Publication Date: 2022-12-31
• Subjects: Social media -- Covid-19 -- public awareness -- geographical disparities -- linguistic disparities; Geographic information systems -- Periodicals; Sustainable development -- Information technology -- Periodicals; Social planning -- Information technology -- Periodicals; 910.285
• DOI: 10.1080/17538947.2022.2070677
• Languages: English
• ISSNs: 1753-8947

Abstract

ABSTRACT: The Covid-19 has presented an unprecedented challenge to public health worldwide. However, residents in different countries showed diverse levels of Covid-19 awareness during the outbreak and suffered from uneven health impacts. This study analyzed the global Twitter data from January 1st to June 30 th, 2020, to answer two research questions. What are the linguistic and geographical disparities of public awareness in the Covid-19 outbreak period reflected on social media? Does significant association exist between the changing Covid-19 awareness and the pandemic outbreak? We established a Twitter data mining framework calculating the Ratio index to quantify and track awareness. The lag correlations between awareness and health impacts were examined at global and country levels. Results show that users presenting the highest Covid-19 awareness were mainly those tweeting in the official languages of India and Bangladesh. Asian countries showed more disparities in awareness than European countries, and awareness in Eastern Europe was higher than in central Europe. Finally, the Ratio index had high correlations with global mortality rate, global case fatality ratio, and country-level mortality rate, with 21-31, 35-42, and 13–18 leading days, respectively. This study yields timely insights into social media use in understanding human behaviors for public health research.