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Legal Network Science: Modeling, Measuring, and Mapping Relational Data in Law
Legal Network Science: Modeling, Measuring, and Mapping Relational Data in Law

Fri, 29 Sept

|

Zoom

Legal Network Science: Modeling, Measuring, and Mapping Relational Data in Law

Corinna Coupette (Max Planck Institute for Informatics/Bucerius Center for Legal Technology and Data Science)

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Time & Location

29 Sept 2023, 15:00

Zoom

About the event

Title: Legal Network Science: Modeling, Measuring, and Mapping Relational Data in Law

Abstract: Networks are everywhere. Lawyers use them to get to work (infrastructure networks), to seek advice (social networks), and to do research (information networks). They craft them (citation networks), oversee them (financial networks), and fight them (criminal networks). Upon closer inspection, almost anything can be modeled as a network: a collection of entities, combined with a collection of relationships between those entities. Legal network science studies how legal phenomena can be represented as networks and investigates what we can gain from their quantification and visualization. This lecture introduces the network perspective on law and teaches the basics of legal network science, with a focus on its potential to enrich legal scholarship.

Corinna Coupette studied law at Bucerius Law School and Stanford Law School, completing her First State Exam in Hamburg in 2015. She obtained a PhD in law from Bucerius Law School and a BSc in computer science from LMU Munich, both in 2018, as well as an MSc in computer science from Saarland University in 2020. Her legal dissertation, which introduces legal network science to German legal discourse, was awarded the Bucerius Dissertation Award in 2018 and an Otto Hahn Medal of the Max Planck Society in 2020. Corinna is currently a research associate at the Max Planck Institute for Informatics, a fellow at the Bucerius Center for Legal Technology and Data Science, and a guest at the Max Planck Institute for Tax Law and Public Finance. She was awarded the Caroline von Humboldt Prize for outstanding female junior scientists in 2022, and will defend her PhD in computer science on expressive methods for exploring complex graph data in October 2023.

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