Social media users’ attitudes toward cyberbullying during the COVID-19 pandemic: associations with gender and verification status - Li, Lifang; Zhou, Jiandong; McManus, Sally; Stewart, Robert; Roberts, Angus (Frontiers in Psychology, 2024)
Social media platforms such as Twitter and Weibo facilitate both positive and negative communication, including cyberbullying. Empirical evidence has revealed that cyberbullying increases when public crises occur, that such behavior is gendered, and that social media user account verification may deter it. However, the association of gender and verification status with cyberbullying is underexplored. This study employed social role theory, the Barlett and Gentile Cyberbullying Model, and general strain theory to examine the influence of Weibo users' gender, verification status, and expression of affect and anger in posts on cyberbullying attitudes. Its focus was to investigate how these factors differed between posts supporting and opposing the cyberbullying of COVID-19 cases during the pandemic. We applied text classification to identify pro-cyberbullying and anti-cyberbullying posts. Then we applied a standardized mean difference method finding significantly more emotions in pro-cyberbullying posts than in anti-cyberbullying posts. Additionally, among pro-cyberbullying posts, posts by verified female users contained more anger-related words than other users. The findings from this study can enhance researchers' algorithms for identifying cyberbullying attitudes, refine the characterization of cyberbullying behavior using real-world social media data through the integration of the mentioned theories, and help government bodies improve their cyberbullying monitoring especially in the context of public health crises.