Cyberbullying on Chinese social media: Language features and influence factors in comments on key opinion leaders' posts

The rapid development of information and communication technologies contributes to the growth of social media channels, which also bring some problems such as cyberbullying. Previous studies have analyzed the prevalence and consequences of cyberbullying and the detection and prevention of it. However, little research pays attention to cyberbullying on Chinese social media. This research uses the content analysis method to analyze cyberbullying on one of the biggest social media platforms in China, Weibo, focusing on language features and factors that influence the frequency of cyberbullying language in comments on key opinion leaders' (KOLs) posts. The findings reveal that most cyberbullying language on Weibo appears in the form of mildly offensive or ordinary words with special meanings and offensive references, rather than directly offensive words. In addition, this research found that KOL type and post content type interact to affect the frequency of cyberbullying language on Weibo. Overall, this research has made a valuable contribution to cyberbullying research.