Media’s Voice in the Noise of Covid-19 Outbreak in the United States


  • Sahar Javed M.Phil. Scholar (Applied Linguistics) University of Management and Technology, Pakistan Author



CDA, Corpus Linguistics, Covid-19 Corpus by Sketch Engine, English Corpora


This research explores the effect of media broadcasting during the covid-19 outbreak in the United States. To find out facts and figures related to broadcasting news, a methodology based on corpus linguistics and CDA is used for analyzing data. The data is taken from the covid-19 corpus by Sketch Engine, where verb collocates of the keyword “pandemic” were chosen to reveal prosodies behind the covid-19 outbreak. Moreover, verb collocates were categorized into four themes e.g. coronavirus outbreak, coronavirus transmission, death toll, and isolation. The frequencies of these categories are investigated through English Corpora, which is a monitor corpus, giving regular updates on the covid-19 situation. While two highly frequent verb collocates “pandemic caused and pandemic occurs” are analyzed in more detail by checking out concordances in a qualitative way. The study sheds light on the media’s positive role in making people aware of the deadliest outcomes of coronavirus. However, fear of misinformation remains, which can be resolved by accessing authentic media sources and by neglecting conspiracy theories.




How to Cite

Sahar Javed. (2020). Media’s Voice in the Noise of Covid-19 Outbreak in the United States. University of Chitral Journal of Linguistics and Literature, 4(II), 88-106.

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