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Aggressive behaviour of anti-vaxxers and their toxic replies in English and Japanese

Social Work

Aggressive behaviour of anti-vaxxers and their toxic replies in English and Japanese

K. Miyazaki, T. Uchiba, et al.

This study reveals the aggressive online tactics of anti-vaxxers on Twitter, showcasing their toxic responses to those with differing beliefs. Conducted by Kunihiro Miyazaki, Takayuki Uchiba, Kenji Tanaka, and Kazutoshi Sasahara, the findings highlight significant differences in behavior between English and Japanese tweets, providing crucial insights into countering online aggression.

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~3 min • Beginner • English
Abstract
The anti-vaccine movement has gained traction in many countries since the COVID-19 pandemic began. However, their aggressive behaviour through replies on Twitter—a form of directed messaging that can be sent beyond follow-follower relationships—is less understood, and even less is known about the language use differences of this behaviour. We conducted a comparative study of anti-vaxxers' aggressive behaviours by analysing a longitudinal dataset of COVID-19 tweets in English and Japanese. We found two common features across these languages. First, anti-vaxxers most actively transmit targeted messages or replies to users with different beliefs, especially to neutral accounts, with significantly toxic and negative language, and these replies are often directed to posts about vaccine operations. Second, influential users with many followers and verified accounts are more likely to receive the most toxic replies from the anti-vaxxers. However, pro-vaccine accounts with a few followers receive highly toxic replies in English, which is different from the Japanese case. These results provide insights into both language-dependent and independent counter-measures against anti-vaxxers' aggressive behaviour.
Publisher
Humanities and Social Sciences Communications
Published On
Jul 28, 2022
Authors
Kunihiro Miyazaki, Takayuki Uchiba, Kenji Tanaka, Kazutoshi Sasahara
Tags
anti-vaxxers
Twitter
toxic replies
COVID-19
language differences
online behavior
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