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Unsupervised and supervised text similarity systems for automated identification of national implementing measures of European directives

Rohan Nanda, Giovanni Siragusa, Luigi Di Caro, Guido Boella, Lorenzo Grossio, Marco Gerbaudo & Francesco Costamagna

Artificial Intelligence and Law 27 (2):199-225 (2019)

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Algorithmic disclosure rules.Fabiana Di Porto - 2023 - Artificial Intelligence and Law 31 (1):13-51.details During the past decade, a small but rapidly growing number of Law&Tech scholars have been applying algorithmic methods in their legal research. This Article does it too, for the sake of saving disclosure regulation failure: a normative strategy that has long been considered dead by legal scholars, but conspicuously abused by rule-makers. Existing proposals to revive disclosure duties, however, either focus on the industry policies (e.g. seeking to reduce consumers’ costs of reading) or on rulemaking (e.g. by simplifying linguistic intricacies). (...) Download Export citation Bookmark 1 citation
The promise and pitfall of automated text-scaling techniques for the analysis of jurisprudential change.Arthur Dyevre - 2020 - Artificial Intelligence and Law 29 (2):239-269.details I consider the potential of eight text-scaling methods for the analysis of jurisprudential change. I use a small corpus of well-documented German Federal Constitutional Court opinions on European integration to compare the machine-generated scores to scholarly accounts of the case law and legal expert ratings. Naive Bayes, Word2Vec, Correspondence Analysis and Latent Semantic Analysis appear to perform well. Less convincing are the performance of Wordscores, ML Affinity and lexicon-based sentiment analysis. While both the high-dimensionality of judicial texts and the validation (...) Download Export citation Bookmark

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