A Close Examination of the 2016 Dallas and Baton Rouge Police Killers: Identifying Potential Risk Factors and Influences for Copycat Violence

Two of the worst targeted attacks on American police officers in recent history occurred within eleven days of each other. Although it seems clear their proximity was not merely attributable to chance, the connection between these incidents, and the implications for understanding copycat violence, have never been fully explored. This study analyzes the perpetrators of these attacks from a “thresholds of violence” perspective, which suggests the first actor in a sequence is more likely to be disturbed and violence prone, while subsequent actors are typically less disturbed but more socially influenced. Results suggest the thresholds model has both merits and limits. The first attacker did have more psychological problems and violence in his past, and the second did seem more influenced by violent role models. However, there were also many similarities between them, and both attacked due to a combination of internal and external factors. If this study's findings are generalizable, higher risks of becoming a copycat offender may exist for individuals who have (1) personal similarities with previous attackers, (2) a history of psychological problems, (3) a history of interest in violent actors, and (4) recent escalation in their online behavior. Recommendations are offered for future research, offender profiling, and violence prevention.

Predicting Serial Stranger Rapists: Developing a Statistical Model From Crime Scene Behaviors

Stranger rapes are the most difficult cases to solve for the police, especially when a serial rapist is involved. Recent research in offender profiling has focused on generating inferences between crime scene variables and offender characteristics to aid the police investigation. This study aims to develop an empirical model to predict a new case of a serial stranger rapist by analyzing a Spanish sample of 231 one-off and 38 serial sexual offenders. A multivariate logistic regression model that included eight significant crime-related variables was able to predict whether an unknown offender is a one-off or serial rapist based only on the victim’s account. The predictive validity of the model was tested using receiver operating characteristic (ROC) analysis and the result of AUC value indicated a medium predictive capacity. The final model correctly classifies nearly 80% of serial stranger rapist cases. The implications of these findings for criminal investigation are discussed.

Predicting rapist type based on crime-scene violence, interpersonal involvement, and criminal sophistication in U.S. stranger rape cases

Stranger rape cases are one of the most difficult sexual assault crimes to solve for law enforcement. This study aimed to compare crime-scene characteristics between serial rapists and single-victim rapists in stranger rape cases and build a predictive model to predict rapist type. An archival database of released sex offenders included 385 who committed stranger rapes. Of those, 244 were single-victim rapists and 141 were serial rapists. The single-victim rapists were significantly more likely to have violently themed crime-scene characteristics than serial rapists, whereas serial rapists were significantly more likely than single-victim rapists to engage in criminally sophisticated behavior and induce participation from their victims. A logistic regression using 10 crime-scene characteristics correctly identified 75.8% of cases as perpetrated by either single-victim or serial rapists. The most significant predictors of rapist type were whether the offender digitally penetrated their victim, whether the offender choked their victim, whether they were at a new/unknown location or whether they threatened their victim. The implications of these results are that they benefit law enforcement in the investigation of stranger rape cases by potentially narrowing down their suspect pool and add to the classification of stranger rapists in offender profiling literature.

Simplifying Research Oriented to Practitioners and Policymakers: A Case Study of Predictive Modelling with Naive Bayes

The study examines the applicability of Naïve Bayes in predictive classification modelling using a case study of cybercrime victimization data. The goal of which was a targeted presentation of the benefits of Bayesian analysis in crime research geared to policymakers. The method is assessed using a Model-Comparison Approach and model performance metrics. The study shows that Naïve Bayes can be useful in predictive classification where the target population is small or difficult to acquire such as offender profiling and analysis of high crime areas. This is important as it provides a plausible option to traditional Frequentist methods, that overcome statistical limitations and provides results in a form easily conveyable to policymakers. Further, the conditional probability data produced makes future prediction transparent and can foster confidence in predicted outcomes. In particular, Directed Acyclic Graph can be easily used to represent the Naïve Bayes output allowing visualization of the relationships between variables.

Psychological Profiling of Criminals in Violent Crime Investigations in Nigerian Criminal Justice System

The Nigerian criminal justice system is not entirely ignorant or unaware of the use and the merits of the application of criminal profiling as a tool in crime investigation. The technique was introduced to help law enforcement agencies solve serious crimes such as serial rape or murder and to a lesser extent arson and property crime. At the heart of profiling lies the belief that by combining psychological principles with crime scene analysis, it is possible to identify the likely characteristics of a perpetrator. However, criminal profiling in Nigeria has not nearly reached the level of recognition, functionality, or institutionalization that it has attained in other jurisdictions. This study aims to examine the feasibility and the practicality of offender profiling in a criminal investigation of violent crimes with a particular focus on the Nigerian criminal justice system. It will also give an expository critique of the loopholes and impediments in the Nigerian criminal justice system and ways criminal profiling can fill up these holes. The research methods employed in this study include a combination of both primary and secondary sources. The work highlighted the effectiveness of this field and thus concluded that criminal investigative analysis should be effectively immersed into the justice system and should also receive as much recognition as it has in other jurisdictions especially in the United States and in major parts of Europe.

APPLICATION OF PROFILING TO COMBAT CYBER CRIME

The article is devoted to the study of current problems of application of advanced methods of profiling in the process of combating cybercrime by units of the National Police. The fight against cybercrime has recently become increasingly important, as there has been a significant increase in the number of cybercrimes. Ukrainian cyber police units must use the most modern methods to combat such crimes. One such method is profiling, which is an important tool for investigating crimes, including information crimes. It allows us to classify cybercriminals, understand their habits and technologies and aims to identify the perpetrator. Due attention is not paid to psychological aspects quite often in operational and investigative activities, resulting in the problem of diagnosis and assessment of the offender. Profiling allows to solve this problem and to increase efficiency of professional activity of divisions of cyber police of National police of Ukraine. But profiling is not used practically in the activities of these units in this time, although the use of profiling in the investigation of cybercrime is quite common in the world's leading countries. Therefore, we aimed to consider the problems of application of advanced profiling techniques in the process of combating cybercrime in the activities of cyber police units, as well as to provide suggestions for improving the current legislation. None of the existing legal documents of our state provides for the use of profiling in the activities of cyber police. Underestimation of capabilities of profiling in cyber police units of the National Police of Ukraine requires rethinking currently. Profiling technologies can be successfully implemented in the activities of operational units of the National Police, including cyber police units, due to it combat crime will be more effectively. It is advisable to add to the existing search measures at the legislative level such a measure as "operational profiling" to this end, that will allow to widely use its capabilities.