Collecting and Connecting
Searching for relevant legal information increasingly resembles looking for a needle in a haystack. The law is more digitally accessible than ever, yet the volume of case law continues to grow and legal rules and decisions are fragmented across national and international legal layers. As a result, it is becoming harder to know where to begin and which judgments actually matter.
This dissertation explores how methods from data science can help bring more structure to this large and fragmented body of case law. It focuses on citations: references judges make to earlier judgments, legislation, or treaties. These citations connect judicial decisions and show how legal authority and principles develop over time. They do not only signal which decisions are influential, but also form part of the legal reasoning through which courts justify their judgments.
By systematically analysing citations, patterns and influential decisions become visible. The research combines traditional doctrinal legal analysis with computational techniques such as automated text analysis and network analysis. It examines how citations can be collected, how influential decisions can be identified, and how international legal norms influence national legal systems through case law.
The results show that these techniques can support legal research by making large bodies of case law easier to navigate and helping researchers identify possible “needles”. Citations reveal where legal authority concentrates and which decisions play an important role. At the same time, technology cannot replace legal judgment: computational methods uncover patterns and connections, but interpretation and legal assessment remains a human task.