A Multinetwork and Machine Learning Examination of Structure and Content in the United States Code

A Multinetwork and Machine Learning Examination of Structure and Content in the United States Code

This paper introduces a novel linked structure-content representation of federal statutory law in the United States and analyzes and quantifies its structure using tools and concepts drawn from network analysis and complexity studies. The organizational component of our representation is based on th...

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Bibliographic Details
Main Authors: Keith Carlson, Faraz Dadgostari, Michael A. Livermore, Daniel N. Rockmore
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Physics
Subjects:
multinetwork
statutory network
United States Code
topic modeling
assortativity
law search
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2020.625241/full

Internet

https://www.frontiersin.org/articles/10.3389/fphy.2020.625241/full

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