Nicola Lettieri

A computational approach for the experimental study of EU case law: analysis and implementation

In recent years, the encounter between network analysis (NA) and Law has issued new challenges both on a scientific and application level. If, on the one hand, it is fostering new computational-inspired approaches to visualize, retrieve, manipulate and analyze legal information, on the other hand, it is inspiring the creation of innovative tools allowing legal scholars without technical skills to start dealing with NA and visual analytics on their own. This paper presents an ongoing research project aiming to explore how approaches and techniques at the boundaries between Network analysis, Legal informatics and Visualization can help shedding new light into legal matters. The attention is focused, on EuCaseNet, an online toolkit allowing legal scholars to apply NA and visual analytics techniques to the entire corpus of EU case law.

Computational Social Science, the Evolution of Policy Design and Rule Making in Smart Societies

In the last 20 years, the convergence of different factors—the rise of the complexity of science, the “data deluge” and the advances in information technologies—triggered a paradigm shift in the way we understand complex social systems and their evolution. Beyond shedding new light onto social dynamics, the emerging research area of Computational Social Science (CSS) is providing a new rationale for a more scientifically-grounded and effective policy design. The paper discusses the opportunities potentially deriving from the intersection between policy design issues and CSS methods. After a general introduction to the limits of traditional policy-making and a brief review of the most promising CSS methodologies, the work deals with way in which the insights potentially offered by CSS can concretely flow in policy choices. The attention is focused, to this end, on the legal mechanisms regulating the formulation and the evaluation of public policies. Our goal is two-fold: sketch how the project of a “smart society” is connected to the evolution of social sciences and emphasize the need for change in the way in which public policies are conceived of, designed and implemented.

Visualization of Music Plagiarism: Analysis and Evaluation

Nowadays plagiarism is an interesting and debated topic in different fields. In music, the plagiarism is a very common phenomenon which touch the vast amounts of money that music melodies are able to generate in todays pop music market. In a music composition, the melody is assumed to be the most significant factor in a courts decision about whether a new music composition is an illegitimate version of a pre-existing composition. Despite the wide-spread belief that there is a fixed and trivial number of corresponding notes between two melodies, the similarity analysis is a very complex process. In this paper we address the plagiarism in pop music, and specifically, we study whether visualization can facilitate the task of discovering melodic similarities among musical songs. To investigate this, we defined three representations to show the melodic relations among songs. We performed a user study in which subjects performed different tasks on a song collection using these representations to investigate which one is best in terms of intuitiveness and accuracy. Results of the study provided us with positive feedback as well as further directions to explore.

Distributed Agent-Based Simulation and GIS: An Experiment with the Dynamics of Social Norms

In the last decade, the investigation of the social complexity has witnessed the rise of Computational Social Science, a research paradigm that heavily relies upon data and computation to foster our understanding of social phenomena. In this field, a key role is played by the explanatory and predictive power of agent-based social simulations that are showing to take advantage of GIS, higher number of agents and real data. We focus GIS based distibuted ABMs. We observed that the density distribution of agents, over the field, strongly impact on the overall performances. In order to better understand this issue, we analyzes three different scenarios ranging from real positioning, where the citizens are positioned according to a real dataset to a random positioning where the agent are positioned uniformly at random on the field. Results confirm our hypothesis and show that an irregular distribution of the agents over the field increases the communication overhead. We provide also an analytic analysis which, in a 2-dimensional uniform field partitioning, is affected by several parameters (which depend on the model), but is also influenced by the density distribution of agents over the field. According to the presented results, we have that uniform space partitioning strategy does not scale on GIS based ABM characterized by an irregular distribution of agents.

The Legal Macroscope. Experimenting with visual legal analytics

This work presents Knowlex, a web application designed for visualization, exploration, and analysis of legal documents coming from different sources. Understanding the legal framework relating to a given issue often requires the analysis of complex legal corpora. When a legal professional or a citizen tries to understand how a given phenomenon is disciplined, his attention cannot be limited to a single source of law but has to be directed on the bigger picture resulting from all the legal sources related to the theme under investigation. Knowlex exploits data visualization to support this activity by means of interactive maps making sense out of heterogeneous documents (norms, case law, legal literature, etc.). Starting from a legislative measure (what we define as Root) given as input by the user, the application implements two visual analytics functionalities aiming to offer new insights on the legal corpus under investigation. The first one is an interactive node graph depicting relations and properties of the documents. The second one is a zoomable treemap showing the topics, the evolution, and the dimension of the legal literature settled over the years around the norm of interest. The article gives an overview of the research so far conducted presenting the results of a preliminary evaluation study aiming at evaluating the effectiveness of visualization in supporting legal activities as well as the effectiveness of Knowlex, the usability of the proposed system, and the overall user satisfaction when interacting with its applications.

Music Plagiarism at a Glance: Metrics of Similarity and Visualizations

The plagiarism is a debated topic in different fields and in particular in music, given the huge amount of money that music is able to generate. Moreover, it is controversial aspect in the laws field given the subjectivity of the judges that have to pronounce on a suspicious case. Automatic detection of music plagiarism is fundamental to overcome these limits by representing an useful support for judges during their pronouncements and an important result to avoid musicians to spend more time in court than on composing and playing music.In this paper we address this issue by defining a new metric to discover pop music similarity and we study whether visualization can assist domain experts in judging suspicious cases. We describe a user study in which subjects performed different tasks on a song collection using different visual representations to investigate which one is best in terms of intuitiveness and accuracy. Results provided us with positive feedback about our choices and some useful suggestions for future directions.

Ex Machina: Analytical platforms, Law and the Challenges of Computational Legal Science

Over the years, computation has become a fundamental part of the scientific practice in several research fields that goes far beyond the boundaries of natural sciences. Data mining, machine learning, simulations and other computational methods lie today at the hearth of the scientific endeavour in a growing number of social research areas from anthropology to economics. In this scenario, an increasingly important role is played by analytical platforms: integrated environments allowing researchers to experiment cutting-edge data-driven and computation-intensive analyses. The paper discusses the appearance of such tools in the emerging field of computational legal science. After a general introduction to the impact of computational methods on both natural and social sciences, we describe the concept and the features of an analytical platform exploring innovative cross-methodological approaches to the academic and investigative study of crime. Stemming from an ongoing project involving researchers from law, computer science and bioinformatics, the initiative is presented and discussed as an opportunity to raise a debate about the future of legal scholarship and, inside of it, about the challenges of computational legal science.

Agents Shaping Networks Shaping Agents: Integrating Social Network Analysis and Agent-Based Modeling in Computational Crime Research

The paper presents a recent development of an interdisciplinary research exploring innovative computational approaches to the scientific study of criminal behavior. The attention is focused on an attempt to combine social network analysis and agent-based modelling into CrimeMiner, an experimental framework that seamlessly integrates document-enhancement, visualization and network analysis techniques to support the study of criminal organizations. Our goal is both methodological and scientific. We are exploring how the synergy between ABM and SNA can support a deeper and more empirically grounded understanding of the complex dynamics taking place within criminal organizations between the individual/behavioral and social/structural level.

Correction to: A computational approach for the experimental study of EU case law: analysis and implementation

The author would like to correct the errors in the publication of the original article. The corrected details are given below for your reading.