During the COVID-19 pandemic, "Chinese Virus" emerged as a controversial term for coronavirus. To some, it may seem like a neutral term referring to the physical origin of the virus. To many others, however, the term is in fact attaching ethnicity to the virus. In this paper, we attempt to shed light on the term's real-world usage on Twitter. Using sentiment feature analysis and topic modeling, we reveal substantial differences between the use of the controversial terms such as "Chinese virus " and that of the non-controversial terms such as "COVID-19" . For example, tweets using controversial terms contain a higher percentage of anger as well as negative emotions. They also point to China more frequently. Our results suggest that while the term "Chinese virus " could be interpreted either as neutral or racist, its usage on social media leans strongly towards the latter .
During the COVID-19 pandemic, "Chinese Virus" emerged as a controversial term for coronavirus. To some, it may seem like a neutral term referring to the physical origin of the virus. To many others, however, the term is in fact attaching ethnicity to the virus. While both arguments appear reasonable, quantitative analysis of the term's real-world usage is lacking to shed light on the issues behind the controversy. In this paper, we attempt to fill this gap. To model the substantive difference of tweets with controversial terms and those with non-controversial terms, we apply topic modeling and LIWC-based sentiment analysis. To test whether "Chinese Virus " and "COVID-19" are interchangeable, we formulate it as a classification task, mask out these terms, and classify them using the state-of-the-art transformer models. Our experiments consistently show that the term "Chinese Virus " is associated with different substantive topics and sentiment compared with "COVID-19" and that the two terms are easily distinguishable by looking at their context .
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on Twitter. Using sentiment feature analysis and topic modeling, we reveal substantial differences between the use of the controversial terms such as
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that of the non-controversial terms such as
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. For example, tweets using controversial terms contain a higher percentage of anger as well as negative emotions. They also point to China more frequently. Our results suggest that while
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could be interpreted either as neutral or racist, its usage on social media leans strongly towards the latter
is associated with different substantive topics and sentiment compared with "COVID-19" and that the two terms are easily distinguishable by looking at their context