A Corpus-Based Critical Discourse Analysis on Cyber Stigmatization -----A Case of Microblogging Discourse on BMW Car Crash

Abstract

Cyber stigmatization has become an increasingly common phenomenon on social media, which usually involves the topics of culture, gender, race, illness and disease. Individuals or collective identities who are stigmatized usually feel different and devalued by others. The present study is conducted from the perspective of Critical Discourse Analysis, assisted by corpus linguistics software, which attempts to reveal the discourse power behind cyber stigmatization by discussing netizens’ emotions and ideologies in the microblogging discourse on BMW Car Crash in Nanjing. With the quantitative and qualitative analysis of 4857 comment collected on Weibo platform under the assistant of AntConc and KHcoder, the findings suggest that: (1) The discussion of network events usually goes through a topic-shift process, and an expansion of discussion area; (2) Many grass-roots netizens get a relatively strong discourse power when expressing opinions on network. They tend to stigmatize a certain social group by stereotypical ideas; (3) Different social status and limited power in real life make netizens generate a strong desire for equality. It is recommended that government should strictly use legal right and resource to guide netizens to analyze problems rationally, so as to reduce the biased and malicious phenomena of “labelling” and “stigmatization”.