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

Authors :
Lifang Li
Jiandong Zhou
Sally McManus
Robert Stewart
Angus Roberts
Source :
Frontiers in Psychology, Vol 15 (2024)
Publication Year :
2024
Publisher :
Frontiers Media S.A., 2024.

Abstract

IntroductionSocial 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.MethodsThis 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.ResultsOur 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.DiscussionThe 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.

Details

Language :
English
ISSN :
16641078
Volume :
15
Database :
Directory of Open Access Journals
Journal :
Frontiers in Psychology
Publication Type :
Academic Journal
Accession number :
edsdoj.bea48bd74bfe4d9cb045aac6bab92dbc
Document Type :
article
Full Text :
https://doi.org/10.3389/fpsyg.2024.1395668