Bots Amplify and Redirect Hate Speech in Online Discourse About Racism During the COVID-19 Pandemic

种族主义 政治 社会学 社会化媒体 大流行 性别研究 政治学 2019年冠状病毒病(COVID-19) 法学 医学 病理 传染病(医学专业) 疾病
作者
Joshua Uyheng,Daniele Bellutta,Kathleen M. Carley
出处
期刊:Social media and society [SAGE]
卷期号:8 (3) 被引量:29
标识
DOI:10.1177/20563051221104749
摘要

Online talk about racism has been salient throughout the COVID-19 pandemic. Yet while such social media conversations reflect existing tensions in the offline world, the same discourse has also become a target for information operations aiming to heighten social divisions. This article examines Twitter discussions of racism in the first and sixth months since COVID-19 was accorded pandemic status by the World Health Organization and uncovers dynamic associations with bot activity and hate speech. Humans initially constituted the most hateful accounts in online conversations about racism in March, but in August, bots dominated hate speech. Over time, greater bot activity likewise amplified levels of hate speech a week later. Moreover, while discourse about racism in March primarily featured an organic focus on racial identities like Asian and Chinese, we further observed a bot-dominated focus in August toward political identities like president, Democrat, and Republican. Although hate speech targeting Asian groups remained present among racism discussions in August, these findings suggest a bot-fueled redirection from focusing on racial groups at the onset of the pandemic to targeting politics closer to the 2020 US elections. This work enhances understanding of the complexity of racism discussions during the pandemic, its vulnerability to manipulation through information operations, and the large-scale quantitative study of inorganic hate campaigns in online social networks.

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