From Yellow Peril to Model Minority: Asian stereotypes in social media during the COVID-19 pandemic

Xinyu Wang, Maggie Wu, Sarah Rajtmajer

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Heightened racial tensions during the COVID-19 pandemic contributed to the increase and rapid propagation of online hate speech towards Asians. In this work, we study the relationship between the racist narratives and conspiracy theories that emerged related to COVID-19 and historical stereotypes underpinning Asian hate and counter-hate speech on Twitter, in particular the Yellow Peril and model minority tropes. We find that the pandemic catalyzed a broad increase in discourse engaging with racist stereotypes extending beyond COVID-19 specifically. We also find that racist narratives and conspiracy theories which emerged during the pandemic and gained widespread attention were rooted in deeply-embedded Asian stereotypes. In alignment with theories of idea habitat and processing fluency, our work suggests that historical stereotypes provided an environment vulnerable to the racist narratives and conspiracy theories which emerged during the pandemic. Our work offers insight for ongoing and future anti-racist efforts.

Original languageEnglish (US)
Title of host publicationWebSci 2023 - Proceedings of the 15th ACM Web Science Conference
PublisherAssociation for Computing Machinery
Number of pages9
ISBN (Electronic)9798400700897
StatePublished - Apr 30 2023
Event15th ACM Web Science Conference, WebSci 2023 - Austin, United States
Duration: Apr 30 2023May 1 2023

Publication series

NameACM International Conference Proceeding Series


Conference15th ACM Web Science Conference, WebSci 2023
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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