A corpus-assisted discourse analysis of Taiwanese students’ sentiments toward Asianphobia on the news amid Covid-19
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Abstract
The anti-Chinese racist slurs and violence toward anyone who bears physical resemblance to a Chinese have escalated at the time the Coronavirus aka Covid-19 has globally spread its wrath. For Taiwanese university students who were also impacted by Covid-19 as their opportunity to travel and study abroad has been put to a halt, raising their awareness of the dangers of racism amid the pandemic has never been more important. This study draws on the students’ feedback on class activity that revolves around language and culture, conflict and resolution. The self-drawn corpus was therefore based on the collected students’ written responses. Critical discourse analysis based on corpus linguistics (Baker et al., 2008) using Voyant Tools (Sinclair & Rockwell, 2016), a web-based text analysis tool, was conducted to investigate word patterns that rose from collocations and concordance data, and the correlational impact of these linguistic devices. These results were then interpreted using critical discourse analysis (CDA) theoretical framework of van Dijk (1984, 2015), Fairclough (1995, 2001) and Wodak (2001) to evaluate the students’ attitudes and social representations that they share. The findings suggest a high frequency of the lemma “Taiwanese” and the collocation “Taiwan can help” signifying a strong sense of pride as an overwhelming majority felt that Taiwan is successfully leading the fight against Covid-19, thus disassociating themselves from the “Chinese mainlanders.” Yet underneath this bold statement lies their deepest concern–a sense of fear for their own safety.
Keywords: corpus discourse analysis, sentiment analysis, Asianphobia, racism