Corpus driven analysis of news reports about Covid-19 in a Malaysian online newspaper

Abstract

Covid-19 was declared a global pandemic by the World Health Organization on 11th March, 2020. Scientists and researchers immediately took interests to find a vaccine. While researchers in various discipline, particularly in medicine, began to study about the virus to help us understand the situation from various perspectives, there is limited research on linguistics analysis to date about Covid-19. Therefore, the present study aims to contribute to research in linguistics about Covid-19, by employing corpus-driven approach for data analysis. Online newspaper reports about Covid-19 were downloaded from the Star online from March 1st to March 31st, 2020. A total of 1018 news reports were processed and analysed, with 140 themes being identified.100 top collocates with the MI score set at a minimum of 5, using AntConc software revealed that verb and noun collocates co-occurred frequently with the node word Covid-19. Generally, the collocates reflect fear, anxiety and uncertainty that majority of Malaysians feel. have. It also shows how the virus is taking a toll on Malaysia and Malaysians with regards to economy and social life. On the other hand, some of the collocates portrayed the government to be in total control of the situation, despite the threat to health and economic situations in the country. Suggestions for future research about Covid-19 include comparison of several newspaper reports from English newspapers in Malaysia, analysis of news report during extended movement control order (ECMO) in Malaysia or discourse analysis of crisis communication by political leaders in ASEAN.