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Social media users’ attitudes toward cyberbullying during the COVID-19 pandemic: associations with gender and verification status

Li, L., Zhou, J., McManus, S. ORCID: 0000-0003-2711-0819 , Stewart, R. & Roberts, A. (2024). Social media users’ attitudes toward cyberbullying during the COVID-19 pandemic: associations with gender and verification status. Frontiers in Psychology, 15, article number 1395668. doi: 10.3389/fpsyg.2024.1395668


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 aims to address this gap by examining how Weibo users’ gender, verification status, and expression of affect and anger in posts influence cyberbullying attitudes. Specifically, it investigates how these factors differ between posts pro- and anti-cyberbullying of COVID-19 cases during the pandemic.

This study utilized social role theory, the Barlett and Gentile Cyberbullying Model, and general strain theory as theoretical frameworks. We applied text classification techniques to identify pro-cyberbullying and anti-cyberbullying posts on Weibo. Subsequently, we used a standardized mean difference method to compare the emotional content of these posts. Our analysis focused on the prevalence of affective and anger-related expressions, particularly examining variations across gender and verification status of the users.

Our text classification identified distinct pro-cyberbullying and anti-cyberbullying posts. The standardized mean difference analysis revealed that pro-cyberbullying posts contained significantly more emotional content compared to anti-cyberbullying posts. Further, within the pro-cyberbullying category, posts by verified female users exhibited a higher frequency of anger-related words than those by 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.

Publication Type: Article
Additional Information: Copyright © 2024 Li, Zhou, McManus, Stewart and Roberts. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Publisher Keywords: cyberbullying, COVID, gender, verification status, emotional responses
Subjects: H Social Sciences > H Social Sciences (General)
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
T Technology > T Technology (General)
Departments: School of Policy & Global Affairs
School of Policy & Global Affairs > Violence and Society Centre
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