"Go eat a bat, Chang!": On the Emergence of Sinophobic Behavior on Web Communities in the Face of COVID-19
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Abstract (arXiv)
The outbreak of the COVID-19 pandemic has changed our lives in unprecedented ways. In the face of the projected catastrophic consequences, many countries have enacted social distancing measures in an attempt to limit the spread of the virus. Under these conditions, the Web has become an indispensable medium for information acquisition, communication, and entertainment. At the same time, unfortunately, the Web is being exploited for the dissemination of potentially harmful and disturbing content, such as the spread of conspiracy theories and hateful speech towards specific ethnic groups, in particular towards Chinese people since COVID-19 is believed to have originated from China. In this paper, we make a first attempt to study the emergence of Sinophobic behavior on the Web during the outbreak of the COVID-19 pandemic. We collect two large-scale datasets from Twitter and 4chan's Politically Incorrect board (/pol/) over a time period of approximately five months and analyze them to investigate whether there is a rise or important differences with regard to the dissemination of Sinophobic content. We find that COVID-19 indeed drives the rise of Sinophobia on the Web and that the dissemination of Sinophobic content is a cross-platform phenomenon: it exists on fringe Web communities like dspol, and to a lesser extent on mainstream ones like Twitter. Also, using word embeddings over time, we characterize the evolution and emergence of new Sinophobic slurs on both Twitter and /pol/. Finally, we find interesting differences in the context in which words related to Chinese people are used on the Web before and after the COVID-19 outbreak: on Twitter we observe a shift towards blaming China for the situation, while on /pol/ we find a shift towards using more (and new) Sinophobic slurs.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Apr 2020.
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Citing papers per year: 2021: 4; 2022: 0; 2023: 0; 2024: 0; 2025: 1.
5 papers.
- 2021Online Hate: Behavioural Dynamics and Relationship with Misinformationcited by 3
- 2021How COVID-19 Is Changing Our Language : Detecting Semantic Shift in Twitter Word Embeddingscited by 2
- 2025Evolving Hate Speech Online: An Adaptive Framework for Detection and Mitigationcited by 1
- 2021Beyond a binary of (non)racist tweets: A four-dimensional categorical detection and analysis of racist and xenophobic opinions on Twitter in early Covid-19cited by 0
- 2021Detecting Propaganda on the Sentence Level during the COVID-19 Pandemiccited by 0
- 2025Evolving Hate Speech Online: An Adaptive Framework for Detection and Mitigation15 Feb 2025
- 2021Detecting Propaganda on the Sentence Level during the COVID-19 Pandemic31 Jul 2021
- 2021Beyond a binary of (non)racist tweets: A four-dimensional categorical detection and analysis of racist and xenophobic opinions on Twitter in early Covid-1918 Jul 2021
- 2021Online Hate: Behavioural Dynamics and Relationship with Misinformation28 May 2021
- 2021How COVID-19 Is Changing Our Language : Detecting Semantic Shift in Twitter Word Embeddings15 Feb 2021