Public perception of COVID-19's global health crisis on Twitter until 14 weeks after the outbreak.

Because language represents advanced aspects of human cognition, studying linguistic styles and figurative meaning have proven effective in measuring embodied cognition about the external world. This article defines the most worrisome topics people discussed from Weeks 1 to 14 after the outbreak and...

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Published in:Digital Scholarship in the Humanities Vol. 36; no. 3; pp. 509 - 525
Main Authors: Abdo, Muhammad S, Alghonaim, Ali S, Essam, Bacem A
Format: Article
Published: Oxford University Press / USA Sep2021
Subjects:
Online Access:View this record in EBSCOhost
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      dt: Sep2021
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        atl: Public perception of COVID-19's global health crisis on Twitter until 14 weeks after the outbreak.
      aug:
        au:
          Abdo, Muhammad S
          Alghonaim, Ali S
          Essam, Bacem A
        affil:
          English Language Resource Center, Al-Azhar University , Egypt
          Department of English Language and Translation, Qassim University , Saudi Arabia
          Department of Computer Science, Cairo University , Egypt
      su:
        COVID-19 pandemic
        Public opinion
        World health
        COVID-19
        Word frequency
        Crisis management
        Anxiety
        Microblogs
      sug:
        subj:
          COVID-19 pandemic
          Public opinion
          World health
          COVID-19
          Word frequency
          Crisis management
          Anxiety
          Microblogs
      ab: Because language represents advanced aspects of human cognition, studying linguistic styles and figurative meaning have proven effective in measuring embodied cognition about the external world. This article defines the most worrisome topics people discussed from Weeks 1 to 14 after the outbreak and compares the message delivered by the literal use of words to the figurative use of metaphoric expressions. We bootstrapped representative data from Twitter over 14 weeks since the inception of the outbreak to be analyzed thematically using the Linguistic Inquiry and Word Count (LIWC) 2015 software as well as corpus tools. The MetaNet database, corpus tools, and manual annotation were used to detect expressions that can be linguistically mapped to the formalized list of conceptual metaphors. The most frequently tagged themes included 'the outbreak of the pandemic, its epidemiology, its prophylaxis measures, national and world economies, media', as well as the 'signs and symptoms of COVID-19'. Although LIWC-based analysis showed English-speaking tweeters maintained high levels of analytical thinking, elevated levels of anger, anxiety, and doubtfulness, there were discrepancies and improper conceptualization of the clinical picture of the pandemic.
      pubtype: Academic Journal
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    language: English
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      custom: © 2019 EADH: The European Association for Digital Humanities.
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      holder: Oxford University Press / USA
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          year: 2021
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