SOPHIA

The Iraqi Insurgency (2003–2011) has commonly been characterized as demonstrating the tendency for violence to cluster and diffuse at the local level. Recent research has demonstrated that insurgent attacks in Iraq cluster in time and space in a manner similar to that observed for the spread of a disease. The current study employs a variety of approaches common to the scientific study of criminal activities to advance our understanding of the correlates of observed patterns of the incidence and contagion of insurgent attacks. We hypothesize that the precise patterns will vary from one place to another, but that more attacks will occur in areas that are heavily populated, where coalition forces are active, and along road networks. To test these hypotheses, we use a fishnet to build a geographical model of Baghdad that disaggregates the city into more than 3000 grid cell locations. A number of logistic regression models with spatial and temporal lags are employed to explore patterns of local escalation and diffusion. These models demonstrate the validity of arguments under each of three models but suggest, overall, that risk heterogeneity arguments provide the most compelling and consistent account of the location of insurgency. In particular, the results demonstrate that violence is most likely at locations with greater population levels, higher density of roads, and military garrisons

Examining the Relationship Between Road Structure and Burglary Risk Via Quantitative Network Analysis

OBJECTIVES: To test the hypothesis that the spatial distribution of residential burglary is shaped by the configuration of the street network, as predicted by, for example, crime pattern theory. In particular, the study examines whether burglary risk is higher on street segments with higher usage potential. METHODS: Residential burglary data for Birmingham (UK) are examined at the street segment level using a hierarchical linear model. Estimates of the usage of street segments are derived from the graph theoretical metric of betweenness, which measures how frequently segments feature in the shortest paths (those most likely to be used) through the network. Several variants of betweenness are considered. The geometry of street segments is also incorporated—via a measure of their linearity—as are several socio-demographic factors. RESULTS: As anticipated by theory, the measure of betweenness was found to be a highly-significant predictor of the burglary victimization count at the street segment level for all but one of the variants considered. The non-significant result was found for the most localized measure of betweenness considered. More linear streets were generally found to be at lower risk of victimization. CONCLUSIONS: Betweenness offers a more granular and objective means of measuring the street network than categorical classifications previously used, and its meaning links more directly to theory. The results provide support for crime pattern theory, suggesting a higher risk of burglary for streets with more potential usage. The apparent negative effect of linearity suggests the need for further research into the visual component of target choice, and the role of guardianship

Does the configuration of the street network influence where outdoor serious violence takes place? Using space syntax to test Crime Pattern Theory

OBJECTIVES: To examine the effect of the physical layout of the street network on the spatial distribution of outdoor serious violence. Crime pattern theory predicts crime would be more prevalent on more connected, accessible or traveled street segments, as these will be more likely to fall within an offender’s awareness space. METHODS: The distribution of incidents of outdoor murder, attempted murder and other near-lethal violent crimes that occurred in one London (UK) borough (N = 447 offenses) was analyzed. The space syntax methodology was used to estimate the to- and through-movement potential of individual street segments. RESULTS: Regression analyses showed higher levels of integration (a measure of to-movement potential) and choice (through-movement potential) were associated with greater odds of a street segment containing at least one crime. Risk was also higher for segments located near to segments with the highest global choice values. In contrast, connectivity (the number of other segments a street segment is adjacent to) was negatively associated with crime occurrence. CONCLUSIONS: As predicted, the configuration of the street network was associated with the spatial distribution of outdoor serious violence. Crime reduction measures should be targeted at high-choice street segments (typically main arteries) and segments nearby

A systematic review of crime facilitated by the consumer Internet of Things

The nature of crime is changing — estimates suggest that at least half of all crime is now committed online. Once everyday objects (e.g. televisions, baby monitors, door locks) that are now internet connected, collectively referred to as the Internet of Things (IoT), have the potential to transform society, but this increase in connectivity may generate new crime opportunities. Here, we conducted a systematic review to inform understanding of these risks. We identify a number of high-level mechanisms through which offenders may exploit the consumer IoT including profiling, physical access control and the control of device audio/visual outputs. The types of crimes identified that could be facilitated by the IoT were wide ranging and included burglary, stalking, and sex crimes through to state level crimes including political subjugation. Our review suggests that the IoT presents substantial new opportunities for offending and intervention is needed now to prevent an IoT crime harvest

Role of the street network in burglars' spatial decision-making

Explaining why crime is spatially concentrated has been a central theme of much criminological research. Although various theories focus on neighborhood social processes, environmental criminology asserts that the physical environment plays a central role by shaping people's activity patterns and the opportunities for crime. Here, we test theoretical expectations regarding the role of the road network in shaping the spatial distribution of crime and, in contrast to prior research, disentangle how it might influence offender awareness of criminal opportunities and the supply of ambient guardianship. With a mixed logit (discrete choice) model, we use data regarding (N = 459) residential burglaries (for the first time) to model offender spatial decision-making at the street segment level. Novel graph theory metrics are developed to estimate offender awareness of street segments and to estimate levels of ambient guardianship, distinguishing between local and nonlocal guardianship. As predicted by crime pattern theory, novel metrics concerning offender familiarity and effort were significant predictors of residential burglary location choices. And, in line with Newman's (1972) concept of defensible space, nonlocal (local) pedestrian traffic was found to be associated with an increase (decrease) in burglary risk. Our findings also demonstrate that "taste" preferences vary across offenders, which presents a challenge for future research to explain

Potential uses of Numerical Simulation for the Modelling of Civil Conflict

This paper explores ways in which civil conflict can be simulated using numerical methods. A general two-party model of conflict is developed by extending an approach proposed by [Christia, F., (2012), Alliance Formation in Civil Wars, Cambridge University Press, New York], which is based on a metric of the 'relative power' that exists between the state and a rebel group. Various definitions of relative power are considered and one of these is chosen to illustrate different types of two-sided armed conflict, namely direct-fire, guerrilla and asymmetric warfare. The additional suggestion of Christia that random or stochastic events can lead to unexpected conflict outcomes is also further extended in this paper. The inclusion in the model of terms describing concurrent rebel recruitment of civilians and state deployment of troops are then described. Examples are presented for various hypothetical cases. It is demonstrated that numerical simulation techniques have great potential for modelling civil war. The Christia approach is shown to provide an excellent basis from which numerical models of civil conflict can be built and from which the progress of a conflict can usefully be visualised graphically

Household occupancy and burglary: A case study using COVID-19 restrictions

INTRODUCTION: In response to COVID-19, governments imposed various restrictions on movement and activities. According to the routine activity perspective, these should alter where crime occurs. For burglary, greater household occupancy should increase guardianship against residential burglaries, particularly during the day considering factors such as working from home. Conversely, there should be less eyes on the street to protect against non-residential burglaries. METHODS: In this paper, we test these expectations using a spatio-temporal model with crime and Google Community Mobility data. RESULTS: As expected, burglary declined during the pandemic and restrictions. Different types of burglary were, however, affected differently but largely consistent with theoretical expectation. Residential and attempted residential burglaries both decreased significantly. This was particularly the case during the day for completed residential burglaries. Moreover, while changes were coincident with the timing and relaxation of restrictions, they were better explained by fluctuations in household occupancy. However, while there were significant decreases in non-residential and attempted non-residential burglary, these did not appear to be related to changes to activity patterns, but rather the lockdown phase. CONCLUSIONS: From a theoretical perspective, the results generally provide further support for routine activity perspective. From a practical perspective, they suggest considerations for anticipating future burglary trends

A Systematic Review of the Criminogenic Potential of Synthetic Biology and Routes to Future Crime Prevention

Synthetic biology has the potential to positively transform society in many application areas, including medicine. In common with all revolutionary new technologies, synthetic biology can also enable crime. Like cybercrime, that emerged following the advent of the internet, biocrime can have a significant effect on society, but may also impact on peoples' health. For example, the scale of harm caused by the SARS-CoV-2 pandemic illustrates the potential impact of future biocrime and highlights the need for prevention strategies. Systematic evidence quantifying the crime opportunities posed by synthetic biology has to date been very limited. Here, we systematically reviewed forms of crime that could be facilitated by synthetic biology with a view to informing their prevention. A total of 794 articles from four databases were extracted and a three-step screening phase resulted in 15 studies that met our threshold criterion for thematic synthesis. Within those studies, 13 exploits were identified. Of these, 46% were dependent on technologies characteristic of synthetic biology. Eight potential crime types emerged from the studies: bio-discrimination, cyber-biocrime, bio-malware, biohacking, at-home drug manufacturing, illegal gene editing, genetic blackmail, and neuro-hacking. 14 offender types were identified. For the most commonly identified offenders (>3 mentions) 40% were outsider threats. These observations suggest that synthetic biology presents substantial new offending opportunities. Moreover, that more effective engagement, such as ethical hacking, is needed now to prevent a crime harvest from developing in the future. A framework to address the synthetic biology crime landscape is proposed

Geographic patterns of diffusion in the 2011 London riots

Surprisingly little research has examined the localised diffusion of riots within cities. In this paper, we investigate such patterns during the 2011 London riots, and consider how they changed as police numbers increased. Understanding how offences spread in space and time can provide insights regarding the mechanisms of contagion, and of the risk of events spreading between contiguous areas. Using spatial–temporal grids of varying resolution, and a Monte Carlo simulation, we compare observed patterns with those expected assuming the timing and location of events are independent. In particular, we differentiate between four space–time signatures: “flashpoints” of disorder which appear out of nowhere, “containment” whereby already affected areas experience further events, “escalation” whereby rioting continues in affected areas and spreads to those nearby, and “relocation” whereby the disorder moves from one locality to those adjacent. During the first half of the disorder, fewer counts of relocation diffusion were observed than expected, but patterns of containment, escalation, and flashpoints were all more prominent. For the second half of the disorder, when police capacity increased roughly three-fold, observed patterns did not differ from expectation. Our results show support for theories of spatial contagion, and suggest that there was a degree of coordination amongst rioters. They also show that police activity did not just suppress rioting, but dampened the influence of contagion, without displacement

"Show this thread": policing, disruption and mobilisation through Twitter. An analysis of UK law enforcement tweeting practices during the Covid-19 pandemic

Crisis and disruption are often unpredictable and can create opportunities for crime. During such times, policing may also need to meet additional challenges to handle the disruption. The use of social media by officials can be essential for crisis mitigation and crime reduction. In this paper, we study the use of Twitter for crime mitigation and reduction by UK police (and associated) agencies in the early stages of the Covid-19 pandemic. Our findings suggest that whilst most of the tweets from our sample concerned issues that were not specifically about crime, especially during the first stages of the pandemic, there was a significant increase in tweets about fraud, cybercrime and domestic abuse. There was also an increase in retweeting activity as opposed to the creation of original messages. Moreover, in terms of the impact of tweets, as measured by the rate at which they are retweeted, followers were more likely to ‘spread the word’ when the tweet was content-rich (discussed a crime specific matter and contained media), and account holders were themselves more active on Twitter. Considering the changing world we live in, criminal opportunity is likely to evolve. To help mitigate this, policy makers and researchers should consider more systematic approaches to developing social media communication strategies for the purpose of crime mitigation and reduction during disruption and change more generally. We suggest a framework for so doing