Serial Crime Research Articles

Logic of Law: Criminal Profiling Strategy

Criminal profiling is used when making decisions on issues in which the cost of a mistake is a person's freedom or life, so it is essential to choose a rational approach and maintain objectivity. Applying the scientific method is the first step of a chain of steps that can level up the effects of even the most common subtle forms of bias, conscious or unconscious, that are distorted by context and the psychological state of the decision-maker. Criminal profiling is considered as one of the decision support strategies in criminal justice. Based on a unique set of statistical and dynamic data of a sociological survey of 13,010 convicts who are serving sentences in penitentiary institutions in Ukraine, a cluster model was built to determine significant indicators of criminal recidivism. The conducted empirical analysis gives reasons to conclude that the number of previous convictions, the age at the time of the first conviction, conditional convictions, and early releases causes the maximum influence on the probability of criminal recidivism. Criminal profiling does not provide conclusive evidence to solve a case or lead to a new line of investigation, but it cannot be denied that criminal profiling is not valuable in some, albeit exceptional, cases. Criminal profiling is effective in cases involving hostage-taking, rapists, arson, sexual murders, serial crimes, and identifying the authors of threatening letters. The built cluster model simplifies the understanding of criminal behavior and the relationship between the details of the profile of the criminal and provides support for decision-making in criminal justice, for example, when detecting fraudulent actions, predicting the possibility of recidivism, reducing bias when making pre-trial or trial decisions. However, much more research is needed before criminal profiling becomes widely accepted as a reliable forensic tool. One of the following stages of the research is possible like the classification of convicts according to their probable tendency to recidivism based on the analysis of their statistical and dynamic characteristics.

Serial crimes against sexual inviolability and sexual freedom of the individual in the 9th - 17th centuries

Serial crimes against sexual inviolability and sexual freedom of the individual in the 9th - 17th centuries

An optimised approach to near repeat analysis for intelligence driven crime linkage

ABSTRACT Law enforcement and security agencies around the globe have integrated geospatial analysis into their intelligence workflow to profile serial offenders, track suspects, and direct crime reduction/prevention efforts. Expansion to spatio-temporal analyses may yield significant and relevant information to better understand the underlying factors of crime. Among the current spatio-temporal methods to associate crimes is near repeat analysis. The premise of the near repeat phenomenon is that if a given location is the target of a crime, nearby locations will have an increased chance of being targeted for a limited time with the level of risk decaying with distance from the original target and over time. Robust analytical methods were developed to discover and further understand spatio-temporal clustering of crime incidents. The open source nature of these functions facilitate transparency and reproducibility in the analytical method and implementation across agencies/police management systems. Firstly, a new method for near repeat analysis is presented which expands current techniques through graphical linkage of crime incidents given spatio-temporal proximity. Next, this method is used to evaluate the prevalence of near repeats across cities of scale. Given this, a method for determining optimal parameters is presented and utilised to determine the optimal parameters (inter-incident time/distance).

The use of artificial intelligence algorithms in the criminalistic study of criminal activity (on the example of serial crimes)

Since artificial intelligence technologies are firmly embedded in many areas of modern life, it is time to explore in detail their capabilities in criminology in the study of criminal activity. The article describes the experience of developing digital models of serial crimes committed for sexual reasons using artificial intelligence algorithms. The empirical basis of the study was data on 1068 serial crimes, including murder. Methods of mathematical statistics and a number of artificial intelligence algorithms were used for data processing: gradient boosting, neural networks, logistic regression, etc. As a result, typical signs of crimes and natural connections between them, used for training models, presented by artificial intelligence algorithms, are revealed. The obtained decision support systems allow predicting the distance from the crime scene to the place of residence of the offender (accuracy 88.3—93.5 %), the age of the offender (accuracy 80.3 %, confidence interval ±6 years), the presence of a mental illness (accuracy 81.5 %) and criminal record (accuracy 82 %), as well as some other characteristics. According to the results of the study, it is concluded that the methods of mathematical statistics and artificial intelligence can be used in the investigation of crimes, as well as in criminalistics.

Of serial murder and true crime: Some preliminary thoughts on black feminist research praxis and the implications of settler colonialism

Of serial murder and true crime: Some preliminary thoughts on black feminist research praxis and the implications of settler colonialism

The Application of Geographical Analysis in Serial Crimes

In this paper, we use bayes’ theorem to generate two mathematical models for a series of crimes. This series of crimes is a dynamic process, so we regard it as JTC model. In this model, there are some major factors, such as the individual’s vulnerability to crime, the attractiveness of the place of the crime and the utilization of the crime from the place of origin to the place of destination. We combine the bayesian theorem with the JTC model to obtain the mathematical model of geographical distribution. We made full use of the model to predict the location of the next perpetrator in the series.

Images of the European Crisis: Populism and Contemporary Crime TV Series

During the last two decades a dramatic shift in the production and distribution strategies of TV series has taken place on a global level. This article discusses how these broad changes also led to a transformation in the form and the themes of European crime series, which emerge as ideal objects to study the representation of European societies in contemporary popular culture. The article looks at recent serial crime dramas such as La casa de papel, Suburra, and Peaky Blinders, which have abandoned the classic formula of European crime TV series, usually focused on the figure of the detective and primarily addressed to a national audience. Designed for an international market, these series provocatively concentrate on the figure of the criminal and adopt an explicitly sensationalist approach. The article argues that this style and the bleak depiction of European society in these series are both an expression and a critical representation of the rise of populism across the Old Continent.

Linkage analysis using geographical proximity: a test of the efficacy of distance measures

PurposeThe purpose of this paper was to compare the accuracy of linking crimes using geographical proximity between three distance measures: Euclidean (distance measured by the length of a straight line between two locations), Manhattan (distance obtained by summing north-south distance and east-west distance) and the shortest route distances.Design/methodology/approachA total of 194 cases committed by 97 serial residential burglars in Aomori Prefecture in Japan between 2004 and 2015 were used in the present study. The Mann–Whitney U test was used to compare linked (two offenses committed by the same offender) and unlinked (two offenses committed by different offenders) pairs for each distance measure. Discrimination accuracy between linked and unlinked crime pairs was evaluated using area under the receiver operating characteristic curve (AUC).FindingsThe Mann–Whitney U test showed that the distances of the linked pairs were significantly shorter than those of the unlinked pairs for all distance measures. Comparison of the AUCs showed that the shortest route distance achieved significantly higher accuracy compared with the Euclidean distance, whereas there was no significant difference between the Euclidean and the Manhattan distance or between the Manhattan and the shortest route distance. These findings give partial support to the idea that distance measures taking the impact of environmental factors into consideration might be able to identify a crime series more accurately than Euclidean distances.Research limitations/implicationsAlthough the results suggested a difference between the Euclidean and the shortest route distance, it was small, and all distance measures resulted in outstanding AUC values, probably because of the ceiling effects. Further investigation that makes the same comparison in a narrower area is needed to avoid this potential inflation of discrimination accuracy.Practical implicationsThe shortest route distance might contribute to improving the accuracy of crime linkage based on geographical proximity. However, further investigation is needed to recommend using the shortest route distance in practice. Given that the targeted area in the present study was relatively large, the findings may contribute especially to improve the accuracy of proactive comparative case analysis for estimating the whole picture of the distribution of serial crimes in the region by selecting more effective distance measure.Social implicationsImplications to improve the accuracy in linking crimes may contribute to assisting crime investigations and the earlier arrest of offenders.Originality/valueThe results of the present study provide an initial indication of the efficacy of using distance measures taking environmental factors into account.

Serial Crime, Serious Threats? Replicating the ‘Yellow Peril’ in British Popular Crime Fiction

Serial Crime, Serious Threats? Replicating the ‘Yellow Peril’ in British Popular Crime Fiction

A novel random forest approach for imbalance problem in crime linkage

Crime linkage is a challenging task in crime analysis, which is to find serial crimes committed by the same offenders. It can be regarded as a binary classification task detecting serial case pairs. However, most case pairs in the real world are nonserial, so there is a serious class imbalance in the crime linkage. In this paper, we propose a novel random forest based on the information granule. The approach does not resample the minority class or the majority class but concentrates on indistinguishable case pairs at the classification boundary. The information granule is used to identify case pairs that are difficult to distinguish in the dataset and constructs a nearly balanced dataset in the uncertainty region to deal with the imbalanced problem. In the proposed approach, random trees come from the original dataset and the above mentioned nearly balanced dataset. A real-world robbery dataset and some public imbalanced datasets are employed to measure the performance of the approach. The results show that the proposed approach is effective in dealing with class imbalances, and it can be extended to combine with other methods solving class imbalances.

A médiaerőszak által belobbantott tűz – egy szexuális indítékból elkövetett sorozatgyilkosság kriminálpszichológiai szemszögből

A sorozatgyilkosságok rendkívül ritkák, viszont annál nagyobb figyelmet kapnak. Különösen igaz ez a szexuális jellegű esetekre. Magyarországon kis számban fordulnak és fordultak elő ezek a sorozat-bűncselekmények, ezért a figyelem még a szokásosnál is nagyobb. Esettanulmányunk alanya a tiszaföldvári Kovács Péter, aki az egyik legsúlyosabb, bizonyíthatóan szexuális indítékból gyilkoló elkövető volt az 1950–1960-as években, s a martfűi rém néven híresült el. A szocializmus korában magát a sorozatgyilkosság fogalmát sem ismerték, de az ideológiai keretek is szűkek voltak ahhoz, hogy egy bizonyos elkövetőhöz több bűncselekményt is kapcsoljanak. A martfűi rém által elkövetett bűntetteket végül részletesen felderítették. Vallomásai és a bizonyítékok alapján pontosan tudjuk bűncselekményeinek körülményeit, az elkövetés módszereit. Gyermekkori sérüléseivel, traumáival, erőszakos jellegű film- és könyvélményeivel eddig azonban nem foglalkozott a szakirodalom. Kovács Péter életpályáját nézve nyomon követhető, hogyan alakította egy súlyos gyermekkori trauma a nőkhöz való viszonyát, valamint azt, hogy agressziója és erőszakos viselkedése bizonyos filmek és könyvek hatására öltött testet. A 21. században, ötven-hatvan évvel az események után különösen érdekes megvizsgálni, milyen jelenetek erősítették fel az elkövetőben azt a számára ellenállhatatlan érzést, hogy erőszakos bűncselekményeket kelljen elkövetnie a nőkkel szemben.

Unstructured Malay Text Analytics Model in Crime

The concern in crime prevention to realize a safe environment for public’s welfare is one of the central agenda to government authorities. The increasing volume of crime reports with unstructured data that are heavily loaded with text presents the biggest challenge to human experts in analysing the data efficiently as it contains lots of hidden and valuable information such as modus operandi and common crime patterns. The capacity limitations in human information processing demand an effective data analytics model to uncover these hidden and potentially meaningful information from large-scale of data especially in Malay language for improving analysis and supporting decision-making in crime investigation. The objective of this paper is to propose Unstructured Malay Text Analytics Model to support serial crime investigation based on modus operandi patterns. The significance output of this paper is to assist experts especially Royal Malaysia Police in crime investigation based on modus operandi patterns analysis as one of the efforts in reducing rate of crime index.

Crime Spatiotemporal Prediction With Fused Objective Function in Time Delay Neural Network

In the criminology area, to detain the serial criminal, the forthcoming serial crime time, distance, and criminal's biography are essential keys. The main concern of this study is on the upcoming serial crime distance, time, and suspect biographies such as age and nationality. In conjunction with having time delays, the dynamic classifier, like Time Delay Neural Network (TDNN) utilized to perform nonlinear techniques-based predictions. The TDNN classifier system, like Back Propagation Through Time (BPTT) and Nonlinear Autoregressive with Exogenous Input (NARX) are two prominent examples. However, BPTT and NARX techniques are unable to identify the dynamic system by using single-activation functions due to producing lower accuracy. Hence, during the training phase, the direct minimization of the TDNN error can further enhance the single activation function. Thus, this work introduces an enhanced NARX (eNARX) model based on the proposed activation functions of SiRBF via fusion of two functions of the hyperbolic tangent (Tansig) and Radial Basis Function (RBF), in the same hidden layer. If a fusion of activation functions can affect the TDNN error minimization, then fusing of the Tansig and RBF functions can produce a precise prediction for crime spatiotemporal. To evaluate the proposed technique and compared it with existing NARX and BPTT, we utilized five time-series datasets, namely, Dow Jones Index, Monthly River flow in cubic meters per second, Daily temperature, and UKM-PDRM datasets namely, “Suspect & Capture” and “Crime Plotting.” The analysis of the results demonstrated that the proposed eNARX produce higher accuracy in comparison to other techniques of NARX and BPTT. Consequently, the proposed technique provides more effective results for the prediction of commercial serial crime

Возможности использования типологического подхода при расследовании серийных преступлений сексуального характера

The article presents the results of testing the typology of serial sexual killers developed by O.D. Sitkovskaya and L.P. Konysheva, on the materials of criminal cases on detected serial crimes of a sexual nature. The study confirmed the presence of the main psychological features specific to each type of criminals, and the possibility of applying the classification for the investigation of other sexual crimes. In addition, mixed types are identified that combine the signs of two and three types of criminal behaviour. Confirming the main hypothesis of the study, the authors of the article consider it necessary to study further the individual psychological characteristics of criminals belonging to mixed types. As a retrospective analysis of the materials of criminal cases has shown and the regular practice of psychological support of the investigation of crimes of a sexual nature confirms, it is the attackers of a mixed type behaviour that are most difficult to identify through the traditional investigative methods.

Review

Review

The Psychopathology of Serial Killers

Serial criminals have always influenced, with great fascination, the imagination and thoughts of the general public. From the earliest eras of history, such criminal personalities, widely publicized at the time, were personalities that shocked and gave rise to reactions as diverse as possible within society. It has long been considered that a serial killer is a man who cannot satisfy his sadistic sexual instincts and resorts to crime in order to obtain satisfaction. It has been observed, however, that the trigger of the serial crime is much wider, therefore there is a vast typology of serial criminals, which we will discuss in detail in this article.

Understanding the origins of the ring‐necked parakeet in the UK

AbstractThe ring‐necked parakeet Psittacula krameri is one of the best‐known invasive species in the UK. It is also arguably the species whose origins as an invasive have been the subject of the greatest speculation, with explanations ranging from birds escaping from the set of the film ‘The African Queen’ to animals being released in Carnaby Street in London by Jimi Hendrix in the 1960s. Here, we use geographic profiling – a statistical technique originally developed in criminology to prioritise the large lists of suspects typical in cases of serial crime such as murder, rape and arson, but more recently applied to ecology and conservation biology – to analyse the spatial patterns of the ring‐necked parakeet, from the first detailed records in the 1960s to the 21st century and ask whether spatial analysis supports these hypotheses. We show that, despite the undoubted appeal of the different hypotheses concerning their origin, spatial analysis provides no support for any of them, leading us to conclude that the birds' establishment in Britain is more likely to be a consequence of repeated releases and introductions, a view supported by a detailed search of the British Newspaper Archive. More generally, our study shows how geographic profiling can be used to understand the spatial patterns of biological invasions over time.

An approach for understanding offender modus operandi to detect serial robbery crimes

Detecting serial crimes is one of the most challenging tasks in crime analysis. Linking crimes committed by the same criminal can improve the work efficiency of police offices and maintain public safety. Previous crime linkage studies have focused on the crime features of modus operandi (M.O.) but did not address the crime process. In this paper, we proposed an approach for detecting serial robbery crimes based on understanding offender M.O. by integrating crime process information. According to the crime narrative text, a natural language processing method is used to extract the action and object characteristics of the crime process, a dynamic time warping method was introduced in the similarity measurement of these characteristics, and an information entropy method was used to weight the similarity of the action and object characteristics to obtain the comprehensive similarity of criminals’ crime process. A real-world robbery dataset is employed to measure the performance of finding serial crimes after adding the crime process information. According to the results, information about the crime process obtained from the case narrative text has significant separability and can better characterize better the offender’s M.O. Five machine learning algorithms are used to classify the case pairs and identify serial cases and nonserial cases. Based on the crime features, the results show that the addition of crime process information can substantially improve the effect of detecting serial crimes.

Digital Criminology: the Mmethod of Digital Profiling of an Unidentified Criminal's Behavior

The authors examine the specific features of the digital environment to analyze contemporary approaches to the system of instruments of studying illegal actions in cyberspace. They state that law enforcement bodies should adapt key characteristics of the digital environment to the accomplishment of investigation tasks. The authors analyze the possibilities offered by digital profiling and modeling of the digital profile (portrait) of an unidentified criminal through mathematical methods of modeling and prediction in investigating and solving serial crimes, including cybercrimes. An extensive review of Russian and foreign publications is used to study the evolution of scientific ideas regarding the profiling method, which is the basis for the digital profiling of the behavioral model of an unidentified criminal in the digital environment. It is stated that none of the branches of criminal law, including criminology and criminalistics, could alone solve the interdisciplinary problem of the investigation and detection of crimes in the digital environment. The authors prove that it is necessary to integrate the knowledge of these branches and to conduct interdisciplinary research involving experts, i.e. to duly streamline the organization of those activities that together make up the investigation and detection of crimes. Based on the content of the concept «modus operandi», which lies at the heart of building an abstract model of criminal behavior, they conclude that it could be used to investigate and solve crimes in the digital environment and determine the specific features of the content of its structural elements. The comparative analysis of the contents of the key stages of profiling is used to prove the expediency of employing the whole range of logical and mathematical methods of analysis to process and analyze criminological information, which leads to the necessity of both critically reviewing them and finding ways to go beyond the traditional approaches. The authors describe the essence of the mathematical extrapolation method, which is most commonly used in criminology for the quantitative analysis of knowledge regarding objects, phenomena, processes, as well as the possibility of using it in digital profiling. As a result of this research based on the systemic approach, the authors state the objective character of links between the traditional and the digital profiling, point out the existing links and regularities, which allow them to reduce the essence of the examined phenomena to building a model through the recreation, in the process of investigation, of the mental trace pattern and then using it to find the guilty person.

Intuitionistic Fuzzy Multi Criteria Decision Making Approach to Crime Linkage Using Resemblance Function

Serial Crimes cost a lot to our society and leave very appalling impact on our society in psychological level. Furthermore, the investigations are often very troublesome in the absence of reliable evidences. From a large number of criminal cases of similar types it is difficult to find the crimes that were committed by the same offenders. Crime linkage is the step by step process by which an investigator studies and detects the crimes related by common offenders. In this paper, a new idea of resemblance among a set of intuitionistic fuzzy set has been introduced. In addition, an intuitionistic fuzzy multi criteria decision making approach has been used to perform crime linkage analysis. This methodology will enable an investigator to find degree of extent for sharing of a common offender or offenders.