1. From News to Knowledge: Predicting Hate Crime Trends through Event Extraction from Media Content.
- Author
-
Jiangwei Liu, Xiangzhen Jia, You Wu, Jingshu Zhang, and Xiaohong Huang
- Subjects
- *
HATE crimes , *SOCIAL media , *LAW enforcement agencies , *HATE speech , *DATA mining , *ELECTRONIC newspapers - Abstract
Social media platforms have emerged as fertile ground for the proliferation of hate speech, which can exacerbate the dissemination of hate crimes. The Federal Bureau of Investigation UCR Program gathers data on hate crimes and disseminates annual reports to identify national patterns and inform law enforcement agencies and policymakers, these reports often fail to keep pace with urgent demands. Real-time monitoring and predictive analysis of hate crime trends are imperative for more effective prevention and response efforts. This paper presents a framework that leverages information extraction techniques to extract incidents from articles published in The New York Times, enabling accurate prediction of hate crime trends at both the federal and state levels. Experimental findings demonstrate the superiority of our approach compared to other traditional methods. By expanding forecasting approaches for federal and state levels' hate crime trends, this framework offers valuable insights for law enforcement agencies and policymakers. [ABSTRACT FROM AUTHOR]
- Published
- 2024