A Critical Discourse Analysis of Depression in Hong Kong Online English News under COVID -19

2000 words. Topic: A Critical Discourse Analysis of Depression in Hong Kong Online English News under COVID -19 [i will give you my data set and you have to use antconc 4.2.4 to generate data for Corpus analysis and CDA; 2000 words; no AI used] The study aims to explore how Hong Kong online news media depict depression during the COVID-19 pandemic. By analyzing the language used in online news reports on depression conveyed by media outlets from January 1, 2020, to December 31, 2022, the research seeks to uncover the underlying ideologies embedded within the discourse in two English online newspapers over the same pandemic period. This study intends to shed light on how depression is framed and discussed during times of crisis like the COVID-19 pandemic. Hence, the following research question has been identified in accordance with the objectives of this study: (1) What linguistic patterns being used in news reports about depression in Hong Kong online English newspapers during the COVID-19 pandemic in 2020 to 2022? (2) How do these linguistic features in news reports about depression in Hong Kong online English newspapers during the COVID-19 pandemic in 2020 to 2022 reveal or reinforce the underlying social ideologies? [TBC, to fit your analysis content] for your reference: Data for this study was collected from two prominent Hong Kong online English newspapers, namely the South China Morning Post and the Hong Kong Free Press, accessible throughout their website. The first stage of the data collection process involved a keyword search, yielding a total of 278 newspaper articles from the first selection. All included newspaper articles contain two inclusion criteria: (1) the presence of the major search term “depression”, and (2) publication within the two years from January 1, 2020, to December 31, 2022. In the second stage, the data filtration process was conducted by eliminating any irrelevant content and news features, leaving only 64 of them to be used as the data. For specificity, all the newspaper articles were filtrated and any of them were found not to primarily contain keywords of (1) “depress”; (2) “COVID”, “pandemic”, “epidemic” or “coronavirus”, and (3) “mental” was excluded. At the same time, newspaper articles with the exclusion criteria were also eliminated: (1) guest-written posts from the News feature of Opinion and Common/Letters; (2) non-local articles covering only China; (3) articles with an entertainment feature like Style magazine; and (4) articles with irrelevant search term usage in the content of this topic like Business, Economy and Law and Crime, as they may only use depression to express a specific crime case, economic situation or person that is not related to the research topic of mental health issue during COVID-19. This yielded a number of 214 news articles excluded, leaving 64 newspapers for inclusion in the database. Among these, 80% were from the South China Morning Post and 20% from the Hong Kong Free Press. At last, before uploading the data into Antconc 4.2.4, all the articles were manually copied and pasted into plain text format (.txt) as a raw document and a text clean-up in order to remove extratextual information such as advertisement and repeated content.