TY - GEN
T1 - Understanding and Analyzing COVID-19-related Online Hate Propagation Through Hateful Memes Shared on Twitter
AU - Vishwamitra, Nishant
AU - Guo, Keyan
AU - Liao, Song
AU - Mu, Jaden
AU - Ma, Zheyuan
AU - Cheng, Long
AU - Zhao, Ziming
AU - Hu, Hongxin
N1 - Publisher Copyright:
© 2023 Owner/Author(s).
PY - 2023/11/6
Y1 - 2023/11/6
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85190624501
U2 - 10.1145/3625007.3630111
DO - 10.1145/3625007.3630111
M3 - Conference contribution
AN - SCOPUS:85190624501
T3 - Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2023
SP - 103
EP - 107
BT - Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2023
A2 - Aditya Prakash, B.
A2 - Wang, Dong
A2 - Weninger, Tim
PB - Association for Computing Machinery, Inc
T2 - 15th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2023
Y2 - 6 November 2023 through 9 November 2023
ER -