NYC Crime Social and Economic Factors

Crime and motor vehicle collisions aredistinct yet interrelated social phenomena, deeplyinfluenced by demographic distributions, economicdisparities, and systemic urban dynamics. This studyinvestigates the spatial and temporal patterns of crimeand motor vehicle collisions (MVCs) across New YorkCity (NYC), integrating quantitative machine learningtechniques and qualitative socio-economic analysis.This research constructs a unified, structured featureset at both borough and ZIP code levels by leveragingmultiple open-source datasets, including crime,arrests, MVCs, and borough-level census indicators.The findings emphasized the significance of predictiveanalytics for urban safety planning, data governance,law enforcement targeting, and optimizing resources.Ultimately, a combination of structured andunstructured data can give rise to actionable insightsfor real-life urban safety problems, as this research hasjust demonstrated.