| Literature DB >> 35291318 |
Anwar Ouassini1, Mostafa Amini2, Nabil Ouassini3.
Abstract
One of the consequences of the emergence of COVID-19 has been the glaring racial and ethnic disparities that have defined the course of the spread of the virus. As a recent migrant-minority community in China, the Black community's experience has been defined by vulgar racism, exploitation, and stigmatization. In the context of COVID-19, the Black community in China was again a target of multiple racial projects which sought to label their bodies as diseased and physical presence as a threat to the viability and safety of the Han majority. The global response was to mobilize online to expose how the Chinese government is systematically facilitating discriminatory policies against Black migrants in China. In the present paper, we explore how Twitter was utilized to mobilize awareness about anti-Black racism in China. We first present a brief history of African migration to China and then discuss the Han racial ideologies that are inspiring the anti-Black racism. We then use latent Dirichlet allocation as a topic modeling algorithm to extract underlying themes to discuss how anti-Black racism in the COVID-19 context was framed and subsequently challenged by the global community. Finally, we conclude with a brief discussion on COVID-19 and the future of the Black community in China.Entities:
Keywords: African migrants; COVID-19; China; Han racial projects; anti-Black racism
Year: 2022 PMID: 35291318 PMCID: PMC8914295 DOI: 10.1177/0034644621992687
Source DB: PubMed Journal: Rev Black Polit Econ ISSN: 0034-6446
Figure 1.Top 15 most frequent hashtags found in tweets related to “Africans,” “China,” and “COVID.”
Breakdown of LDA-Derived Topics with Example of Keywords.
| Topic | Description | Example keywords |
|---|---|---|
| Topic 1: Micro-level discrimination | Discrimination felt in daily life and the individualistic level by Black migrants in China amid coronavirus pandemic | Racism, African, foreigners, white |
| Topic 2: Transnational grievances | Transnational grievances that involve the Chinese state, as indicated between the connection of keywords such as “Black” and “Taiwan,” which is the focal point of international contention with the likes of the United States | Black, world, Chinese virus, xenophobia, Taiwan is not China |
| Topic 3: Global awareness | Connections are drawn between the local mistreatment of Black migrants in China, and the greater Black Lives Matter movement | Black Twitter, coronavirus, black lives matter |
| Topic 4: Reactionary | Reactionary and direct in its consequential manner, containing a strong anti-Chinese sentiment encouraging organized movement mobilizations, given the mistreatment of Black migrants | China must fall, China must pay, boycott China, Wuhan virus |
Note. LDA = latent Dirichlet allocation.
Figure 2.Visual of the “intertopic distance map” and the 30 most salient terms in the analyzed tweets, using the python package “LDAvis.” Proximity in the distance map is an indication of closeness in the probability distribution and similarity of topics, whereas the individual size of clusters indicates the prominence of the topic.