Social Network Analysis in Predictive Policing

2016-10-11 Computers

Author : Mohammad A. Tayebi
Release : 2016-10-11
Genre : Computers
Kind : eBook
Book Rating : 925/5 ( reviews)

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Book Synopsis Social Network Analysis in Predictive Policing by : Mohammad A. Tayebi

Download or read book Social Network Analysis in Predictive Policing written by Mohammad A. Tayebi. This book was released on 2016-10-11. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on applications of social network analysis in predictive policing. Data science is used to identify potential criminal activity by analyzing the relationships between offenders to fully understand criminal collaboration patterns. Co-offending networks—networks of offenders who have committed crimes together—have long been recognized by law enforcement and intelligence agencies as a major factor in the design of crime prevention and intervention strategies. Despite the importance of co-offending network analysis for public safety, computational methods for analyzing large-scale criminal networks are rather premature. This book extensively and systematically studies co-offending network analysis as effective tool for predictive policing. The formal representation of criminological concepts presented here allow computer scientists to think about algorithmic and computational solutions to problems long discussed in the criminology literature. For each of the studied problems, we start with well-founded concepts and theories in criminology, then propose a computational method and finally provide a thorough experimental evaluation, along with a discussion of the results. In this way, the reader will be able to study the complete process of solving real-world multidisciplinary problems.

Predictive Models for Public Safety Using Social Network Analysis

2015

Author : Mohammad Ali Tayebi
Release : 2015
Genre :
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Predictive Models for Public Safety Using Social Network Analysis by : Mohammad Ali Tayebi

Download or read book Predictive Models for Public Safety Using Social Network Analysis written by Mohammad Ali Tayebi. This book was released on 2015. Available in PDF, EPUB and Kindle. Book excerpt: Crime reduction and prevention is the major concern of law enforcement agencies in order to increase public safety, reduce the crime costs to society and protect the personal integrity and property of citizens. Along with big data analytics, predictive policing which is a new paradigm for crime analysis has been emerging. An important task in predictive policing is analyzing the relationships between offenders to fully understand the criminal collaboration patterns. Law enforcement agencies have long realized the importance of analyzing co-offending networks, networks of offenders who have committed crimes together, for designing prevention and intervention strategies. Despite the importance of co-offending network analysis for public safety, computational methods for analyzing large-scale criminal networks are rather premature. In this research, we study co-offending network analysis as effective tool assisting predictive policing. We start with a formal representation of crime data and co-offending networks to bridge the conceptual gap between abstract crime data level and co-offending network mining. To gain a better understanding of co-offending networks we thoroughly study their structural properties. Specifically, how centrality measures can be employed to identify key players of co-offending networks to disrupt these networks. Then, we propose an algorithmic solution for detecting organized crime groups from a social network analysis perspective. We explore predicting criminal collaborations from two angles. First, given partial information about offenders involved in a crime incident, our proposed approach assists in investigating the most probable suspects in that incident. Second, we propose a supervised learning framework for co-offence prediction. Finally, we propose a random walk based method for crime location prediction which is personalized for every offender by using spatial information about offenders and the co-offending networks structure. The efficacy of the proposed methods are experimentally evaluated using a large crime dataset representing five years of police arrest-data for the regions of the Province of British Columbia which are policed by the RCMP, and compared to other existing methods.

Predictive Policing and Artificial Intelligence

2021-02-25 Computers

Author : John McDaniel
Release : 2021-02-25
Genre : Computers
Kind : eBook
Book Rating : 389/5 ( reviews)

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Book Synopsis Predictive Policing and Artificial Intelligence by : John McDaniel

Download or read book Predictive Policing and Artificial Intelligence written by John McDaniel. This book was released on 2021-02-25. Available in PDF, EPUB and Kindle. Book excerpt: This edited text draws together the insights of numerous worldwide eminent academics to evaluate the condition of predictive policing and artificial intelligence (AI) as interlocked policy areas. Predictive and AI technologies are growing in prominence and at an unprecedented rate. Powerful digital crime mapping tools are being used to identify crime hotspots in real-time, as pattern-matching and search algorithms are sorting through huge police databases populated by growing volumes of data in an eff ort to identify people liable to experience (or commit) crime, places likely to host it, and variables associated with its solvability. Facial and vehicle recognition cameras are locating criminals as they move, while police services develop strategies informed by machine learning and other kinds of predictive analytics. Many of these innovations are features of modern policing in the UK, the US and Australia, among other jurisdictions. AI promises to reduce unnecessary labour, speed up various forms of police work, encourage police forces to more efficiently apportion their resources, and enable police officers to prevent crime and protect people from a variety of future harms. However, the promises of predictive and AI technologies and innovations do not always match reality. They often have significant weaknesses, come at a considerable cost and require challenging trade- off s to be made. Focusing on the UK, the US and Australia, this book explores themes of choice architecture, decision- making, human rights, accountability and the rule of law, as well as future uses of AI and predictive technologies in various policing contexts. The text contributes to ongoing debates on the benefits and biases of predictive algorithms, big data sets, machine learning systems, and broader policing strategies and challenges. Written in a clear and direct style, this book will appeal to students and scholars of policing, criminology, crime science, sociology, computer science, cognitive psychology and all those interested in the emergence of AI as a feature of contemporary policing.

The Rise of Big Data Policing

2019-11-15 Law

Author : Andrew Guthrie Ferguson
Release : 2019-11-15
Genre : Law
Kind : eBook
Book Rating : 97X/5 ( reviews)

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Book Synopsis The Rise of Big Data Policing by : Andrew Guthrie Ferguson

Download or read book The Rise of Big Data Policing written by Andrew Guthrie Ferguson. This book was released on 2019-11-15. Available in PDF, EPUB and Kindle. Book excerpt: Winner, 2018 Law & Legal Studies PROSE Award The consequences of big data and algorithm-driven policing and its impact on law enforcement In a high-tech command center in downtown Los Angeles, a digital map lights up with 911 calls, television monitors track breaking news stories, surveillance cameras sweep the streets, and rows of networked computers link analysts and police officers to a wealth of law enforcement intelligence. This is just a glimpse into a future where software predicts future crimes, algorithms generate virtual “most-wanted” lists, and databanks collect personal and biometric information. The Rise of Big Data Policing introduces the cutting-edge technology that is changing how the police do their jobs and shows why it is more important than ever that citizens understand the far-reaching consequences of big data surveillance as a law enforcement tool. Andrew Guthrie Ferguson reveals how these new technologies —viewed as race-neutral and objective—have been eagerly adopted by police departments hoping to distance themselves from claims of racial bias and unconstitutional practices. After a series of high-profile police shootings and federal investigations into systemic police misconduct, and in an era of law enforcement budget cutbacks, data-driven policing has been billed as a way to “turn the page” on racial bias. But behind the data are real people, and difficult questions remain about racial discrimination and the potential to distort constitutional protections. In this first book on big data policing, Ferguson offers an examination of how new technologies will alter the who, where, when and how we police. These new technologies also offer data-driven methods to improve police accountability and to remedy the underlying socio-economic risk factors that encourage crime. The Rise of Big Data Policing is a must read for anyone concerned with how technology will revolutionize law enforcement and its potential threat to the security, privacy, and constitutional rights of citizens. Read an excerpt and interview with Andrew Guthrie Ferguson in The Economist.

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