Abstract
Although with some discrepancy, both in common law and in civil law systems, previous judgments play an important role with respect to future decisions. Traditional legal methodologies usually involve the use of manual rather than automatic keyword search mechanisms to retrace the steps of the judicial decision-making. However, these methods are generally highly time-consuming and can be subject to different types of biases. In this work, we present an automated extraction pipeline to map and structure citations in rulings regarding fiscal state aids in the case-law of the Court of Justice of the European Union. In particular, by exploiting the available XML data in the EUR-Lex platform, we built an end-to-end parser based on a set of regular expressions and heuristics, which is able to iteratively extract all citations, finally creating a hierarchical structure of citations with their contextual information at the paragraph level. Such data structure can be projected into a graphical representation, enabling useful visualization and exploration features and insights, such as the diachronic study of the development of specific citations and legal principles over time. Our work suggests how the exploitation and analysis of citation networks through automated means can provide significant tools to support traditional legal methodologies.
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Sartor, G., Santin, P., Audrito, D., Sulis, E., Di Caro, L. (2022). Automated Extraction and Representation of Citation Network: A CJEU Case-Study. In: Guizzardi, R., Neumayr, B. (eds) Advances in Conceptual Modeling. ER 2022. Lecture Notes in Computer Science, vol 13650. Springer, Cham. https://doi.org/10.1007/978-3-031-22036-4_10
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