How Do Arab Tweeters Perceive the COVID-19 Pandemic?

被引:0
作者
Bacem A. Essam
Muhammad S. Abdo
机构
[1] Cairo University,Department of Computer Science
[2] Al-Azhar University,English Language Resource Center (ELRC)
来源
Journal of Psycholinguistic Research | 2021年 / 50卷
关键词
COVID-19; R language; Pandemic; LIWC; Psycholinguistics;
D O I
暂无
中图分类号
学科分类号
摘要
Language reflects several cognitive variables that are grounded in cognitive linguistics, psycholinguistics and sociolinguistics. This paper examines how Arab populations reacted to the COVID-19 pandemic on Twitter over twelve weeks since the outbreak. We conducted a lexicon-based thematic analysis using corpus tools, and LIWC and applied R language’s stylo. The dominant themes that were closely related to coronavirus tweets included the outbreak of the pandemic, metaphysics responses, signs and symptoms in confirmed cases, and conspiracism. The psycholinguistic analysis also showed that tweeters maintained high levels of affective talk, which was loaded with negative emotions and sadness. Also, LIWC’s psychological categories of religion and health dominated the Arabic tweets discussing the pandemic situation. In addition, the contaminated counties that captured most of the attention of Arabic tweeters were China, the USA, Italy, Germany, India, and Japan. At the same time, China and the USA were instrumental in evoking conspiracist ideation about spreading COVID-19 to the world.
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页码:507 / 521
页数:14
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共 51 条
[1]  
Abdelzaher EM(2019)Lexicon-based detection of violence on social media Cognitive Semantics 5 32-69
[2]  
Abdelzaher EM(2019)The systematic adaptation of violence contexts in the ISIS discourse: A contrastive corpus-based study Corpus Pragmatics 3 173-203
[3]  
Abdelzaher EM(2019)Weaponising words: Rhetorical tactics of radicalisation in Western and Arabic countries Journal of Language and Politics 18 893-914
[4]  
Essam BA(2017)Impact of infectious disease epidemics on tuberculosis diagnostic, management, and prevention services: experiences and lessons from the 2014–2015 Ebola virus disease outbreak in West Africa International Journal of Infectious Diseases 56 101-104
[5]  
Ansumana R(2019)Linguistic crisis prediction: An integration of the linguistic category model in crisis communication Journal of Language and Social Psychology 38 650-679
[6]  
Keitell S(2011)Measurement of negativity bias in personal narratives using corpus-based emotion dictionaries Journal of Psycholinguistic Research 40 119-135
[7]  
Roberts GM(2007)Protecting organisation reputations during a crisis: The development and application of situational crisis communication theory Corporate Reputation Review 10 163-176
[8]  
Ntoumi F(2010)The linguistic correlates of conversational deception: Comparing natural language processing technologies Applied Psycholinguistics 31 439-462
[9]  
Petersen E(2016)Stylometry with R: A package for computational text analysis R Journal 8 107-122
[10]  
Ippolito G(2019)When folkloric geopolitical concerns prompt conspiratorial ideation: The case of Egyptian tweeters GeoJournal 84 121-133