Research Group Legal Data Science

The Research Group Legal Data Science applies a quantitative approach to the study of the law. Selected publications can be found below.

Members of the Research Group

Janis Beckedorf

University of Heidelberg

Maximilian Böther

ETH Zürich

Michael J. Bommarito

273 Ventures

Corinna Coupette

MPI Informatics

Dirk Hartung

Bucerius Law School

Daniel Martin Katz

Chicago-Kent College of Law

Publications

GPT Takes the Bar Exam

Michael Bommarito and Daniel Martin Katz

Under Review

SSRN

Rechtsstrukturvergleichung

Corinna Coupette and Dirk Hartung

86 RabelsZ 935 (2022)

RabelsZ SSRN

Sharing and Caring: Creating a Culture of Constructive Criticism in Computational Legal Studies

Corinna Coupette and Dirk Hartung

Accepted, MIT Computational Law Report

SSRN arXiv

Law Smells: Defining and Detecting Problematic Patterns in Legal Drafting

Corinna Coupette, Dirk Hartung, Janis Beckedorf, Maximilian Böther and Daniel Martin Katz

Artif Intell Law (2022)

AI & Law SSRN arXiv

LexGLUE: A Benchmark Dataset for Legal Language Understanding in English

Ilias Chalkidis, Abhik Jana, Dirk Hartung, Michael Bommarito, Ion Androutsopoulos, Daniel Martin Katz and Nikolaos Aletras

ACL Main Conference + Oral Presentation

ACL Anthology SSRN arXiv

Legal Informatics

Daniel Martin Katz, Michael Bommarito and Ron Dolin

Cambridge University Press 2021

CUP Website

Measuring Law Over Time: A Network Analytical Framework with an Application to Statutes and Regulations in the United States and Germany

Corinna Coupette, Janis Beckedorf, Dirk Hartung, Michael Bommarito and Daniel Martin Katz

Front. Phys. 9:658463 (2021)

Paper Conference

Complex Societies and the Growth of the Law

Daniel Martin Katz, Corinna Coupette, Janis Beckedorf and Dirk Hartung

10 Scientific Reports 18737 (2020)

Paper

Open Source