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This goal is undoubtedly a worthy one. Specifically, where the legal sciences have been slow to adopt computational techniques relative to other related disciplines; and more generally, in a climate where increasing volumes of data describing crime and our responses to it often clash with decreasing human resources available to analyse such data. Put simply, those who are tasked with understanding and responding to undesirable behaviour are increasingly being asked to do more with less. As such, it is inevitable that computational techniques will be increasingly leveraged to bear this load.
Presenting research from this important cross-disciplinary field, the editors have curated a total of 20 manuscripts from a variety of international researchers. These contributions range considerably in topic and approach, including discussions of the current state or potential futures of computational studies in law and criminology; the specification and application of computational models for both theory building and policy development; and the novel application of information-extraction, social network and geospatial analysis techniques in the study of criminological phenomena and their associated legal responses.
To illustrate, contributions by Domenico Parisi (Robotic Societies and Law: A Plea for a Robotic and Simulation Science of Legal Phenomena) and in particular Bruce Edmonds (What Social Simulation Might Tell Us about How Law Works) provide a suitable introduction to the types of questions computational social science is well equipped to address within the legal sciences. Importantly, this is achieved at a level that will likely be accessible and inspiring to readers from both computational and legal backgrounds.
Klaus Troitzsch outlines several simulation approaches relevant to the study and development of legislation (Legislation, Regulatory Impact Assessment and Simulation). In particular, Troitzsch focuses on regulatory impact assessment - a technique that aims to assess the impacts of potential legislative change - and for which social simulation seems an eminently suitable tool. Nicola Lettieri and Domenico Parisi present a simple but powerful agent-based model that explores the interplay of ‘other-damaging behaviours’, punishment, deterrence, imitation and learning (Exploring the Effects of Sanctions on Damaging Actions through Artificial Societies: A Simulation Model). Lettieri and Parisi’s model illustrates well the strengths of the agent-based laboratory in enabling important experimentation that would otherwise be difficult to undertake through traditional means. Taking a similar methodological approach but applying it to study spatio-temporal patterns of crime in an urban context, Nick Malleson and colleagues specify a detailed agent-based model of residential burglary (The Leeds Burglary Simulator). Drawing upon a range of criminological theory and real-world data, their model demonstrates how simulation techniques may ultimately inform operational crime prevention activities.
Distinct from these applications of agent-based modelling, contributions by Deborah De Felice et al. (Information Extraction and Social Network Analysis of Criminal Sentences. A Sociological and Computational Approach) and Nicola Lettieri et al. (Text and Social Network Analysis as Investigative Tools: A Case Study) describe substantial research projects that apply a combination of data mining and social network analysis techniques to increase understanding of court processes and criminal networks respectively. Both projects demonstrate a clear commitment of computational and legal scientists to collaborate in developing computational tools useful in a range of applied settings. Finally, contributions by Guido Migliaccio (Computational Sciences, Business Management, Accounting and Law: Potential Intersections) and Ernesto Fabiani (Law and Computational Social Science: Brief Notes of a Civil Procedure Law Scholar) set out both the ends and means by which computational social science may support scholars in the fields of accounting, business management, economics and civil procedure law.
As with any edited collection, this range of topics is both a strength and weakness. Unfortunately, there is also variability in the accessibility of chapters, and in places, difficulties with readability. These issues likely reflect the technical nature of the topics discussed, and the varying nationalities of authors presenting them. However, it is important that such issues be acknowledged in the context of the volume’s aim to present computational social science to a range of researchers, some of whom are likely unfamiliar with its intricacies.
With that said, Law and Computational Social Science does present a body of work sufficiently diverse to stimulate most readers interested in how computational social science can support legal and criminological research. Moreover, this diversity highlights the breadth of potential utility that computational social science has to offer both those who undertake research in the legal sciences and associated disciplines, and those who aim to sculpt and apply policy informed by such research.
Crime and disorder are significant societal problems - exploring the applicability of new techniques in how we measure, analyse, understand and respond to them is of upmost importance. In this regard, computational social science clearly offers both scholars and practitioners alike an array of approaches that can compliment existing methods of legal and criminological enquiry in new and useful ways.
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