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The ubiquity of social media has transformed communication patterns and interactions in contemporary society, allowing individuals to share experiences, thoughts, and opinions on a global scale. However, this unprecedented connectivity has also facilitated the dissemination of hate speech, posing novel challenges for platforms, policymakers, and researchers. This study delves into the dynamics of hate speech diffusion within social media networks, focusing on Twitter as a case study. Through an extensive analysis of retweet behaviors among a subset of hateful users, we investigate the intricate network structures and characteristics that underlie the spread of harmful content. By analyzing network metrics and degree distributions and comparing them with model approximations, we reveal insights into the polarized nature of hate speech propagation, the role of strongly connected components, and the influence of a select few users. The findings highlight the potential for viral spread within closely connected groups and emphasize the need for nuanced approaches to curbing hate speech. Moreover, this study contributes to the broader understanding of information dissemination on social media, paving the way for informed strategies to foster a more responsible and inclusive digital discourse.
Yueqiao Chen (Fri,) studied this question.