MPS

Crime continues to cast a shadow over citizen well-being in big cities today, while also imposing huge economic and social costs. Prevention, early detection and strategic mitigation are all critical to effective policy intervention, especially in domains where coordinated responses are required. Every day, about 10,000 incidents are reported by citizens, recorded and geo-referenced in the London Metropolitan Police Service Computer Aided Dispatch (CAD) database. Today, impending funding cuts bring new pressures for central accountability and improved efficiency, while community empowerment initiatives bring new opportunities and challenges to policing. Timely understanding of how criminality emerges and how crime patterns evolve is crucial to anticipating crime, dealing with it when it occurs and developing public confidence in the police service. It is widely understood that policing, crime and public trust all have strong spatial and temporal dimensions. An integrated approach to space-time analysis is needed in order to analyse crime patterns, police activity patterns and community characteristics, so as to understand and predict the when, where and what of how criminal activities emerge and are sustained. This research will consolidate achievements in integrated spatio-temporal data mining and emergent network complexity to uncover patterning in crime, policing and citizen perceptions at a range of spatial and temporal scales. Each dataset of police movement, crime (and disorder) reported in the CAD, and citizens making '999' calls constitutes a spatio-temporal network (STN), which has its own characteristic patterning and behaviour in space-time, and which interacts with the other STNs. The (geotagged) deployment of police manpower in space and time, the spatio-temporal patterning of crime and disorder, and the perceptions of members of the public are likely to be interlinked to differing extents. The first of these purportedly both anticipates and responds to the second, while the third is a lagged response to the first two, giving reason to anticipate that all three networks should be tightly coupled. The project will first analyse spatio-temporal patterns of individual STNs, then associate the patterns among these STNs via integrated spatio-temporal data mining developed using innovative statistical regression and machine learning. This research will utilise a range of disciplines (crime, geography, geoinformatics, and computer science) to help engineer effective practical solutions to crime problems. It proposes a new method for exploring crime patterns and integrating information on crime and police activity. It systematically addresses a structured programme of analytical issues in spatio-temporal data mining, which are becoming core to Geographical Information Sciences. It will advance the theory, methodology and application of research into network complexity by evaluating the forms and interactions of the networks that characterise crime and other socio-economic phenomena. This will make it possible to not only understand activity networks but also to use them for prediction and decision making. This addresses the aims of RCUK's Global Uncertainties Programme in crime, terrorism, and ideologies and beliefs. It will extend our appreciation of the subtle interplay of different forms of complex systems, in ways that will contextualise tactical and strategic responses to terrorism and organised crime. It will enable intelligent policing of London Met Police by granting unforeseen levels of prediction. The best practice of individual Metropolitan boroughs can be extended to others in the UK. The methodology developed here will be transferrable to other international cities using similar incident report systems. This will directly benefit people who live, work and visit London and those cities to make them feel safe.

The aim of this project is to dramatically improve the quality of immersive social virtual environments (IVEs). By 'quality' we refer to the response of participants to virtual social situations, in particular the extent to which they respond realistically to what they perceive. By 'response' we mean at every measurable level, ranging from non-conscious physiological processes (such as changes in electrodermal activity or heart rate variability) through to overt behavioural, emotional and cognitive responses / including what they report in interviews about their subjective state of mind. By social IVEs we specifically refer to applications where one or more human participants interact with virtual humanoid characters (avatars) in a socially defined context. Specifically, our objectives are to improve the visual appearance of interactive characters and their interactive behaviour especially so that their behaviour responds appropriately to the behaviour of the participants. Third, social IVEs will be constructed that are well-studied in the social psychology literature, and which are of great societal importance, referred to as bystander behaviour in violent emergencies such as in street violence. Finally, these virtual social situations will be used in a series of experimental studies in order to test whether indeed these objectives do improve the quality of response of participants within these social IVEs.One of our goals is to exploit our research in socially useful applications, and thereby also contribute to the growing body of research that uses VEs as a laboratory for social psychological research. In particular we consider the research program of Levine and colleagues at Lancaster on bystander behaviour in violent emergencies. This research program revisits the classic 'bystander effect' in social psychology. The bystander effect suggests that the more witnesses there are to an emergency, the less likely an individual bystander is to intervene. This phenomenon was identified as a consequence of the apparent inaction of 38 witnesses to the brutal rape and murder of Kitty Genovese in New York in 1964. The bystander effect is one of the most robust and reproduced effects in social psychology. However, it lacks practical utility, since for ethical and practical reasons it is not possible to study it scientifically under controlled conditions. In this project we aim to study the bystander effect in the context of virtual environments, where other work has shown that people do tend to respond realistically to virtual social situations.

The aim of this project is to dramatically improve the quality of immersive social virtual environments (IVEs). By 'quality' we refer to the response of participants to virtual social situations, in particular the extent to which they respond realistically to what they perceive. By 'response' we mean at every measurable level, ranging from non-conscious physiological processes (such as changes in electrodermal activity or heart rate variability) through to overt behavioural, emotional and cognitive responses / including what they report in interviews about their subjective state of mind. By social IVEs we specifically refer to applications where one or more human participants interact with virtual humanoid characters (avatars) in a socially defined context. Specifically, our objectives are to improve the visual appearance of interactive characters and their interactive behaviour especially so that their behaviour responds appropriately to the behaviour of the participants. Third, social IVEs will be constructed that are well-studied in the social psychology literature, and which are of great societal importance, referred to as bystander behaviour in violent emergencies such as in street violence. Finally, these virtual social situations will be used in a series of experimental studies in order to test whether indeed these objectives do improve the quality of response of participants within these social IVEs.One of our goals is to exploit our research in socially useful applications, and thereby also contribute to the growing body of research that uses VEs as a laboratory for social psychological research. In particular we consider the research program of Levine and colleagues at Lancaster on bystander behaviour in violent emergencies. This research program revisits the classic 'bystander effect' in social psychology. The bystander effect suggests that the more witnesses there are to an emergency, the less likely an individual bystander is to intervene. This phenomenon was identified as a consequence of the apparent inaction of 38 witnesses to the brutal rape and murder of Kitty Genovese in New York in 1964. The bystander effect is one of the most robust and reproduced effects in social psychology. However, it lacks practical utility, since for ethical and practical reasons it is not possible to study it scientifically under controlled conditions. In this project we aim to study the bystander effect in the context of virtual environments, where other work has shown that people do tend to respond realistically to virtual social situations.

The aim of this project is to dramatically improve the quality of immersive social virtual environments (IVEs). By 'quality' we refer to the response of participants to virtual social situations, in particular the extent to which they respond realistically to what they perceive. By 'response' we mean at every measurable level, ranging from non-conscious physiological processes (such as changes in electrodermal activity or heart rate variability) through to overt behavioural, emotional and cognitive responses / including what they report in interviews about their subjective state of mind. By social IVEs we specifically refer to applications where one or more human participants interact with virtual humanoid characters (avatars) in a socially defined context. Specifically, our objectives are to improve the visual appearance of interactive characters and their interactive behaviour especially so that their behaviour responds appropriately to the behaviour of the participants. Third, social IVEs will be constructed that are well-studied in the social psychology literature, and which are of great societal importance, referred to as bystander behaviour in violent emergencies such as in street violence. Finally, these virtual social situations will be used in a series of experimental studies in order to test whether indeed these objectives do improve the quality of response of participants within these social IVEs.One of our goals is to exploit our research in socially useful applications, and thereby also contribute to the growing body of research that uses VEs as a laboratory for social psychological research. In particular we consider the research program of Levine and colleagues at Lancaster on bystander behaviour in violent emergencies. This research program revisits the classic 'bystander effect' in social psychology. The bystander effect suggests that the more witnesses there are to an emergency, the less likely an individual bystander is to intervene. This phenomenon was identified as a consequence of the apparent inaction of 38 witnesses to the brutal rape and murder of Kitty Genovese in New York in 1964. The bystander effect is one of the most robust and reproduced effects in social psychology. However, it lacks practical utility, since for ethical and practical reasons it is not possible to study it scientifically under controlled conditions. In this project we aim to study the bystander effect in the context of virtual environments, where other work has shown that people do tend to respond realistically to virtual social situations.

Police reports suggest that domestic abuse (DA) has risen as a result of the pandemic, yet there is concern that the share of DA incidents reported may have fallen. When a victim and abuser are quarantined together, calling the police may jeopardize the victim's safety. As a result, greater numbers of victims are increasingly isolated and at risk. So how can victims get help? How can authorities let them know what options are available? Direct messaging can be dangerous, since texts from the police may provoke a controlling abuser. We propose a targeted social media campaign to inform potential high-risk victims about the Silent Solution, a safer option for contacting police. Our approach leverages the wide use of social media, which also poses less risk than direct messaging. Whereas text messages are actively sent, social media adverts are passively received. The study will identify potential high-risk victims and randomly select half for the media campaign. Analysis of DA calls will show whether the approach is effective. If so, it will provide an approach for reaching isolated DA victims, and for giving them options to get help, that will be of value both during quarantine and beyond.