| Abstrakt: |
In contemporary society, 5 major crimes are recognized as significant social issues with negative impacts on both individuals and the nation. This study utilizes spatial big data to analyze the determinants of 5 major crimes in 25 districts of Seoul, taking into account inherent spatial influences. To achieve this, the study examines the spatial distribution of 5 major crimes and compares the fitness of regression models, excluding spatial influences, with geographically weighted Poisson regression model that considers spatial effects. Additionally, empirical analyses are conducted using negative binomial regression and geographically weighted Poisson regression models. Population density, district area, commercial land area ratio, and number of pubs, which appeared significantly among the seven variables in the negative binomial regression, were analyzed to have a positive impact on all districts in the geographically weighted Poisson regression. On the other hand, variables such as the foreigner ratio, CCTV count, and the ratio of multi-household house were not significant, in contrast to previous studies. [ABSTRACT FROM AUTHOR] |
