Spatio-temporal cokriging crime predictions using social media data: a multi-type case study in San Jose, California

The results indicate that incorporating social media data into a spatio-temporal statistical method improves the associations between predicted and actual crime risk, reduced the Root Mean Squared Error (RMSE), and enhanced the identification of crime risk areas for both weekdays and weekends across three crime types compared to the method without the co-variable.