Online citizen petitions related to COVID-19 in South Korean cities: a big data analysis.

Abstract

What do citizens demand of their governing bodies to cope with the spread of emerging infectious diseases after recognizing the growing danger? What are the similarities and differences in political participation via online citizen petitions regarding COVID-19 across cities with different degrees of pandemic experience? This study aims to answer these questions by examining citizen petitions regarding the COVID-19 pandemic in urban areas of South Korea. The pattern of citizens' requests is a part of integrative socio-ecological and political systems with spatial and temporal dimensions. We compare the pattern of online citizen petitions in four Korean cities, namely Seoul, Busan, Daegu, and Incheon, some of which were epicenters of the COVID-19 outbreak. By applying relevant big data analysis techniques such as text mining, topic modeling, and network analysis, we compare the characteristics of citizen petitions on COVID-19 in the four cities, particularly whether (and how) they want financial or welfare support or COVID-19 prevention. We find that cities that experience a rapid spread are likely to have more petitions for prevention than for support. By comparison, cities without such experience are likely to have more petitions for support. This study contributes by tracing citizen and local government interactions in response to emerging infectious diseases by empirically analyzing the related big data on petitions. Policy implications suggest that urban authorities should listen to analyze and respond to the urgent needs of citizens.