The purpose of this study is to explore the associative background information of offensive speech among the participants on Sina Weibo.
Data from 65,321 participants and 83,203 posts from the top 50 “Hot Searches” hashtags on Sina Weibo were analyzed between July 2022 and July 2023. Social network analysis, association analysis and principal component regression were employed to explore the patterns and factors influencing offensive speech.
A layered circular social network structure was observed with two main clusters: center and periphery. Offensive speech is primarily concentrated in these two subsets. In the center cluster, users were more interactive and tended to use offensive language more in comments directed at others. Conversely, users in the periphery cluster were part of less interactive subgroups and often used offensive language in posts to express their opinions. Notably, association analysis revealed that certain user profiles, such as non-VIP users and users with moderate follower counts, were associated with a higher possibility of engaging in offensive posting or commenting.
The research highlights the complex interplay between user behavior, community structure and content dissemination in the context of offensive speech on social media.
