Socially disruptive periods and topics from information-theoretical analysis of judicial decisions | EPJ Data Science | Full Text

Laws and legal decision-making regulate how societies function. Therefore, they evolve and adapt to new social paradigms and reflect changes in culture and social norms, and are a good proxy for the evolution of socially sensitive issues. Here, we use an information-theoretic methodology to quantitatively track trends and shifts in the evolution of large corpora of judicial decisions, and thus to detect periods in which disruptive topics arise. When applied to a large database containing the full text of over 100,000 judicial decisions from Spanish courts, we are able to identify an abrupt change in housing-related decisions around 2016. Because our information-theoretic approach pinpoints the specific content that drives change, we are also able to interpret the results in terms of the role played by legislative changes, landmark decisions, and the influence of social movements.

1 Introduction Technological advances have facilitated the generation and storage of digital documents stemming from human activities, from financial transactions to medical records or drug prescriptions. These digital traces open the door to understanding human behavior in new ways [1]; digital documents allow to analyze the temporal evolution of the interactions between social actors, making it possible to infer the sociological and cultural processes beneath human activities [2]. In this endeavor, computational efforts are critical to automatize the processing and extraction of…

saved by

• saurav kumar

related reading

• The Death of the Legal Subject: How Predictive Algorithms Are (Re)constructing Legal Subjectivityfacctconference.org
• [2306.13000] Apolitical Intelligence? Auditing Delphi's responses on controversial political issues in the USarxiv.org
• [2303.17548] Whose Opinions Do Language Models Reflect?arxiv.org
• AI and prediction of criminal justice risk: revisiting the COMPAS dataset, experiments, and the problem of algorithmic bias and fairnesslink.springer.com
• Microsoft Word - 03_Trites Volume 11 issue 2 Final.docxgmj-canadianedition.ca
• arxiv.org/pdf/2505.24832arxiv.org
• Scaling Laws Do Not Scalearxiv.org
• The impact of AI errors in a human-in-the-loop processlink.springer.com
• Opinion Dynamics: A Comprehensive Overviewar5iv.labs.arxiv.org
• [1509.07175] Exploration and Exploitation of Victorian Science in Darwin's Reading Notebooksarxiv.org
• [1306.6929] Power indices of influence games and new centrality measures for social networksThis work is partially supported by 2009SGR–1137 (ALBCOM).ar5iv.labs.arxiv.org
• Generation and influence of eccentric ideas on social networksnature.com