Before revision:  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 .
After revision:  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" 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 " could be interpreted either as neutral or racist, its usage on social media leans strongly towards the latter .