Understanding and Analyzing COVID-19-related Online Hate Propagation Through Hateful Memes Shared on Twitter




Vishwamitra, Nishant
Guo, Keyan
Liao, Song
Mu, Jaden
Ma, Zheyuan
Cheng, Long
Zhao, Ziming
Hu, Hongxin

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Association for Computing Machinery


Recent studies regarding the COVID-19 pandemic have revealed the widespread propagation of hateful content during this period. While significant research has focused on COVID-19-related online hate in text (e.g., text-based tweets), the role of memes in propagating online hate during the pandemic has been largely overlooked. Memes are a popular mechanism used by Internet users to convey their thoughts and opinions on a variety of topics. However, memes have emerged as an important mechanism through which ideologically potent and hateful content spreads on social media platforms. In this work, we focus on investigating the role of memes in the propagation of online hate during the COVID-19 pandemic. We first collect a novel dataset of 4,001 COVID-19-related hateful memes and their replies over a 3-year period from Twitter. Then, we carry out the first large-scale investigation into the impact of these memes on Twitter users, by studying the psychological reactions of Twitter users to these memes using various text analysis methods. We find that COVID-19-related hateful memes have a significantly greater negative impact on Twitter users in comparison to text-based hateful tweets, and increasing negativity towards such memes over the 3-year period. Our new dataset of COVID-19-related hateful memes and findings from our work pave the way for studying the dissemination and moderation of COVID-19-related online hate through the medium of memes.




Vishwamitra, N., Guo, K., Liao, S., Mu, J., Ma, Z., Cheng, L., . . . Hu, H. (2024). Understanding and Analyzing COVID-19-related Online Hate Propagation Through Hateful Memes Shared on Twitter. Paper presented at the The 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Kusadasi, Turkiye. https://doi.org/10.1145/3625007.3630111


Information Systems and Cyber Security