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During the COVID-19 pandemic, "Chinese Virus" emerged as a controversial termfor coronavirus. To some, it may seem like a neutral term referring to thephysical origin of the virus. To many others, however, the term is in factattaching ethnicity to the virus. While both arguments appear reasonable,quantitative analysis of the term's real-world usage is lacking to shed lighton the issues behind the controversy. In this paper, we attempt to fill thisgap. To model the substantive difference of tweets with controversial terms andthose with non-controversial terms, we apply topic modeling and LIWC-basedsentiment analysis. To test whether "Chinese Virus" and "COVID-19" areinterchangeable, we formulate it as a classification task, mask out theseterms, and classify them using the state-of-the-art transformer models. Ourexperiments consistently show that the term "Chinese Virus" is associated withdifferent substantive topics and sentiment compared with "COVID-19" and thatthe two terms are easily distinguishable by looking at their context.

In the Eyes of the Beholder: Analyzing Social Media Use of Neutral and Controversial Terms for COVID-19