The smart city fever has led to many studies. However, there have been lacks of researches on safety and crisis perception of inhabitants. In this study, we conducted a big data analysis of Namyangju city, a local government in Korea. The data were obtained from Namyangju city social survey, city demographic and civil data from 2009 to 2017. The analysis methods are t-test, time series analysis, and text analysis on safety-related citizens’ petitions in the groups with high and low risk perception. According to the results, the regions where risk perception is high, it shows that safety complaints are more frequently raised. Areas with high risk perception are likely to be new towns or redevelopment areas, given the large number of new arrivals and young age groups. In this case, the problem of traffic safety is an issue connected with the traffic system. The petitions text analysis can more specifically explain the demand for the complaints. We could explain seasonal effects, urban development, and policy responses through analysis of citizens’ petition and time series analysis according to population composition.
Volume 11 | 07-Special Issue
Pages: 1316-1319