Profiling School Shooters: Automatic Text-Based Analysis

The Grievance Dictionary: Understanding threatening language use

This paper introduces the Grievance Dictionary, a psycholinguistic dictionary that can be used to automatically understand language use in the context of grievance-fueled violence threat assessment. We describe the development of the dictionary, which was informed by suggestions from experienced threat assessment practitioners. These suggestions and subsequent human and computational word list generation resulted in a dictionary of 20,502 words annotated by 2318 participants. The dictionary was validated by applying it to texts written by violent and non-violent individuals, showing strong evidence for a difference between populations in several dictionary categories. Further classification tasks showed promising performance, but future improvements are still needed. Finally, we provide instructions and suggestions for the use of the Grievance Dictionary by security professionals and (violence) researchers.

Screening for potential school shooters through the weight of evidence

The challenge of automatically screening for potential school shooters involves several difficulties. In this paper, we present a simple and interpretable methodology for screening for potential school shooters through (1) the psychological textual signature of the shooter and (2) Jaynes approach for measuring the weight of evidence. We have tested our proposed approach on a dataset of texts written by shooters and non-shooters alike (N = 5047). Our major finding is that the methodology can successfully support the screening for potential shooters in interpretable way. The major implication for stakeholders is that there is great potential in developing screening systems for improving the safely of schools. However, developing such a system is a project that must be actualized within an integrated system of “command and control”.

Automated Risk Assessment for School Violence: a Pilot Study

School violence has increased over the past ten years. This study evaluated students using a more standard and sensitive method to help identify students who are at high risk for school violence. 103 participants were recruited through Cincinnati Children's Hospital Medical Center (CCHMC) from psychiatry outpatient clinics, the inpatient units, and the emergency department. Participants (ages 12-18) were active students in 74 traditional schools (i.e. non-online education). Collateral information was gathered from guardians before participants were evaluated. School risk evaluations were performed with each participant, and audio recordings from the evaluations were later transcribed and manually annotated. The BRACHA (School Version) and the School Safety Scale (SSS), both 14-item scales, were used. A template of open-ended questions was also used. This analysis included 103 participants who were recruited from 74 different schools. Of the 103 students evaluated, 55 were found to be moderate to high risk and 48 were found to be low risk based on the paper risk assessments including the BRACHA and SSS. Both the BRACHA and the SSS were highly correlated with risk of violence to others (Pearson correlations>0.82). There were significant differences in BRACHA and SSS total scores between low risk and high risk to others groups (p-values <0.001 under unpaired t-test). In particular, there were significant differences in individual SSS items between the two groups (p-value <0.001). Of these items, Previous Violent Behavior (Pearson Correlation = 0.80), Impulsivity (0.69), School Problems (0.64), and Negative Attitudes (0.61) were positively correlated with risk to others. The novel machine learning algorithm achieved an AUC of 91.02% when using the interview content to predict risk of school violence, and the AUC increased to 91.45% when demographic and socioeconomic data were added. Our study indicates that the BRACHA and SSS are clinically useful for assessing risk for school violence. The machine learning algorithm was highly accurate in assessing school violence risk.

A comprehensive approach to managing threats of violence on a university or college campus

Horrifying, high profile acts of violence on campuses remain relatively rare, nevertheless, academic administrators are required to manage threats of violence on campus on an increasingly regular basis. These threats take two primary forms, those in which the perpetrator and the intended victim(s) are clearly identified, often involving repeated threats and threatening behaviour towards an individual; and those involving anonymous threats to commit acts of larger scale violence. Complicating factors in managing these threats include: fear contagion; mass media and social media attention; responsibilities to all members of the university community sometimes including individuals issuing the threat and the intended victims; demands for safety and security measures that are often at odds with professional advice; and permeable campus boundaries that cause security challenges. This paper considers the changing landscape of threat assessment and risk assessment on university and college campuses and suggests opportunities for partnerships between forensic mental health professionals and academic administrators.