Hostility between men and women on Chinese social media: a content analysis of Sina Weibo with word frequency analysis and topic modeling

Gender-based antagonism is now a severe problem on Chinese social media. It is worthwhile to explore the public discourse on this topic to deal with the issue appropriately. In the current study, I collected 7181 posts containing keywords: gender-based antagonism, hostility toward male/female, and Yang Li. I developed a coding scheme to classify the hashtags about gender-based antagonism into different categories and further collected 10176 comments under the popular posts for each category. Based on the data, I analyzed high-frequency words in these comments and conducted LDA to find salient topics related to hostility toward males/females and Yang Li. Results showed that gender-role stereotype is the most salient category that may incite gender-based antagonism. Three topics were found for hostility toward males/females, and they share similar topics about personal experience and general views; two topics were found for Yang Li. Limitations and implications were discussed, and future work could be done based on data within a larger time span.