Monsuru Adepeju

Manchester Metropolitan University | MMU · Department of Sociology and Criminology

In recent decades, the analysis of different geographic scales for studying the spatial patterning of crime has profoundly deepened our theoretical grasp of crime dynamics. However, a similar investigation is lacking when it comes to the patterning of offender residences, despite there being clear theoretical and empirical reasons for doing so, amo...

There are stark spatial and temporal inequalities in the exposure to crime. Crime concentrates in particular neighbourhoods of cities and at certain times of the day. The novel contribution of this chapter rests in its attention to what happens next. In the context of constrained resource, the deployment of police officers to incidents of crime req...

Street-level crime maps are publicly available online in England and Wales. However, there was initial resistance to the publication of such fine-grained crime statistics, which can lower house prices and increase insurance premiums in high crime neighbourhoods. Identifying the causal effect of public crime statistics is difficult since crime stati...

Crime may affect house prices through mediating causal pathways--such as the destruction of property or victimisation of locals. One mediating pathway is the 'signalling' effect of crime which may decrease house prices in high crime areas due to a perception of increased victimisation or other factors like undesirable neighbours. The public may for...

Generates artificial spatiotemporal (ST) point patterns through the integration of microsimulation (Holm, E., 2017) and agent-based models (Bonabeau, E., 2002). Allows a user to define the behaviours of a set of 'walkers' (agents, objects, persons, etc.) whose interactions with the spatial (landscape) (Quaglietta, L. and Porto, M., 2019) and the te...

Longitudinal clustering techniques are widely deployed in computational social science to delineate groupings of subjects characterized by meaningful developmental trends. In criminology, such methods have been utilized to examine the extent to which micro places (such as streets) experience macro-level police-recorded crime trends in unison. This...

Designed for performing impact analysis of opinions in a digital text document (DTD). The package allows a user to assess the extent to which a theme or subject within a document impacts the overall opinion expressed in the document. The package can be applied to a wide range of opinion-based DTD, including commentaries on social media platforms (s...

This tool analyzes the opinions inherent in a text document relating to a specific subject (A), and assesses the impacts that opinion expressed with respect to another subject (B) have on subject A. This package is specifically designed for application to social media datasets, such as Twitter and Facebook. The utility of the package has been demon...

As the COVID-19 pandemic sweeps across the globe, police forces are charged with new roles as they engage and enforce new policies and laws governing societal behaviours. However, how the police exercise these powers are an important factor in shaping public opinion and confidence concerning their activities across space and time. This research dev...

Objectives: This paper disentangles the degree of concentration and variance in offender residences across different levels of spatial aggregation. Three nested units are analysed simultaneously (and longitudinally) to explore the impact of using different spatial scales, opening prospect for a comparison with existing findings from crime concentra...

Advances a novel adaptation of longitudinal k-means clustering technique for grouping trajectories based on the similarities of their long-term trends and determines the optimal solution based on the Calinski-Harabatz criterion. Includes functions to extract descriptive statistics and generate a visualisation of the resulting groups, drawing method...

The significance of synthetic crime datasets in criminological research cannot be underestimated, as real crime datasets are usually unavailable in many policing jurisdictions, due to reasons such as privacy concerns and the lack of shareable data formats. This study introduces a dynamic microsimulation framework by which a specified spatiotemporal...

The benefits of active travel for individual and urban health, the environment, and society are becoming increasingly apparent (Celis-Morales et al. 2017), and many cities are preparing ambitious walking and cycling plans. However many transport authorities lack strong and actionable evidence to support this investment for a number of reasons, incl...

The spatial and temporal thresholds (K and T) are two key parameters that control the performance of the Prospective Space-Time Scan Statistical (PSTSS) hotspot method. This study proposes an objective function approach, in which the optimal values of K and T that maximise the mean hit rate (a measure of predictive accuracy), are determined. The pr...

This study examines the impacts of two variables; the training data lengths (T) and the aggregation unit sizes (M); on the accuracy of the self-exciting point process (SEPP) model during crime prediction. A case study of three crime types in the South Chicago area is presented, in which different combinations of values of T and M are used for 100 d...

The investigation of repeat and near-repeat (RNR) patterns of sub-categories of burglary crimes is of great importance to law enforcement since a distinct intervention strategy may be suitable in the application to a different sub-category. In this study, the Knox test is used to investigate the RNR patterns within the data set of three different s...

This paper compares two variants of the Knox test in relation to space-time crime pattern analysis. A case study of burglary and ‘stolen-vehicle’ crime da-ta sets of San Francisco city is presented. The comparative analysis shows that while one variant is designed to detect the sizes of the spatio-temporal neighbourhoods at which clustering (hotspo...

The goal of this study is to determine the number of iterations (𝑟) required in a Monte Carlo based space-time interaction analysis of crime data sets, in order to test the adequacy of using a single value of 999 iterations. A case study of burglary crime data sets is presented in which Knox test is used for the analysis of space-time interactions....

With a limited amount of resources, the new practice of predictive policing has exhibited great potential in relation to improving policing efficiency and reducing urban crime levels. The practice of predictive policing involves the use of analytical hotspot methods to identify the likely locations of future crimes, so that pre-emptive steps can be...

The input value for the maximum spatial scan extent (K) of a prospective space-time scan statistical (PSTSS) technique is one important parameter that ensures accurate detection of the predictive hotspot of a geographical point events. Currently, there is no general consensus on how to determine the optimal value of K that maximises the predictive...

The input value for the maximum spatial scan extent (K) of a prospective space-time scan statistical (PSTSS) technique is one important parameter that ensures accurate detection of the predictive hotspot of a geographical point events. Currently, there is no general consensus on how to determine the optimal value of K that maximises the predictive...

Crime, Policing and Citizenship (CPC) – Space-Time Interactions of Dynamic Networks has been a major UK EPSRC-funded research project. It has been a multidisciplinary collaboration of geoinformatics, crime science, computer science and geography within University College London (UCL), in partnership with the Metropolitan Police Service (MPS). The a...

Many physical and sociological processes are represented as discrete events in time and space. These spatio-temporal point processes are often sparse, meaning that they cannot be aggregated and treated with conventional regression models. Models based on the point process framework may be employed instead for prediction purposes. Evaluating the pre...

This study examines the existing metrics used in evaluating the effectiveness of area-based crime hotspots for operational policing. We identified some of the limitations of the metric (i.e. Area-to-Perimeter (AP) ratio) used for measuring compactness of hotspots and then proposed a new improved metric called " Clumpiness Index (CI) ". The case stu...

Background When analytical techniques are used to understand and analyse geographical events, adjustments to the datasets (e.g. aggregation, zoning, segmentation etc.) in both the spatial and temporal dimensions are often carried out for various reasons. The ‘Modifiable Areal Unit Problem’ (MAUP), which is a consequence of adjustments in the spatia...

Detecting crime patterns as they emerge in both space and time can enhance situational awareness amongst security agents and prevent epidemics of crimes in potential problematic areas (Neill and Gorr, 2007). Amongst others, space-time scan statistics (STSS) (Kulldorff et al. 2005) and space -time kernel (Nakaya and Yano, 2010) have been widely used...