Racial Discrimination and Anti-discrimination: The COVID-19 Pandemic’s Impact on Chinese Restaurants in North America

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has seen a rise in racial discrimination against Asian communities, notably the Chinese population. Despite growing research on various aspects of the pandemic, there is a notable gap in understanding its behavioral impact regarding racial discrimination. This study delves into the manifestations of COVID-19-related racial discrimination and antidiscrimination efforts on online platforms using large-scale data sets from Yelp.com and SafeGraph. We specifically examined how the pandemic affected Chinese restaurants compared with non-Chinese ones at different pandemic phases. Our findings are significant; the pandemic triggered an immediate surge in racial discrimination, resulting in a substantial decrease in customers visiting Chinese restaurants. Importantly, we applied advanced text mining and machine learning techniques to analyze user behavior, consistently revealing that increased discrimination prompted users to take antidiscrimination actions on online platforms. This research highlights a tangible form of racial discrimination through reduced patronage of Chinese restaurants and underscores the capacity of consumers to combat discrimination on online platforms. It calls for targeted policy interventions to address and prevent racial discrimination, particularly in the context of public health crises.