Automated detection of school violence using linguistic features

On average, there are 52 violent incidents per school per year. Early identification of high-risk students prior to aggression or violence could help prevent future episodes. While there has been progress in violence prevention, most research still relies on specialized, manual, and time-intensive risk assessments. There are no automated risk-assessment scales to guide risk prevention. Our objective is to develop an Automated RIsk Assessment (ARIA) tool that uses machine learning to predict the risk of violence and aggression using structured interview transcripts from students.