Measuring Law Over Time

Paper and data analysis for "Measuring Law Over Time: A network analytical framework and an application to statutes and regulations in the United States and Germany"

Corinna Coupette, Janis Beckedorf, Dirk Hartung, Michael Bommarito, and Daniel Martin Katz, Measuring Law Over Time, Frontiers in Physics, 2021, https://www.frontiersin.org/articles/10.3389/fphy.2021.658463.

Structure

• analysis: python code to prepare the input data for the graphics and tables presented in the paper
• graphics: graphics and tables presented in the paper; to get the tables into paper-shape, run prettify_tables.py in this folder
• notebooks: jupyter notebooks generating all graphics (and some of the tables) presented in the paper
• results: data for the micro-level connectivity and profiles sections that would otherwise clutter up the graphics folder
• supplements: manually edited supplementary material (law name lists for the German profile case study and cluster family labels)
• writing: the source code of the paper, including a figures folder composing paper figures and tables from the graphics folder

Reproducing the Paper Results

1. It is assumed that you have Python 3.7 installed. (Other versions are not tested.)
2. Set up a virtual environment and activate it. (This is not required but recommended.)
3. Download the data at https://doi.org/10.5281/zenodo.4660133, extract it, so that legal-networks-data is next to the folder of this repository and has the subfolders de, us, and us_reg. Their subfolders must be manually extracted, if needed to run the analysis.
4. Run run_analysis_and_notebooks.sh to install the requirements and run the code.
5. The results are available in this folder writing.

Related Work

Daniel Martin Katz, Corinna Coupette, Janis Beckedorf, and Dirk Hartung, Complex Societies and the Growth of the Law, Sci. Rep. 10 (2020), https://doi.org/10.1038/s41598-020-73623-x

Related Repositories:

• Complex Societies and the Growth of the Law (First Publication Release)
• Legal Data Preprocessing (First Publication Release)
• Legal Data Clustering (First Publication Release)

Related Data: Preprocessed Input Data for Sci. Rep. 10 (2020)