Download This PaperMining the Harvard Caselaw Access Project
69 Pages Posted: 9 Mar 2020 Last revised: 2 Oct 2020
Date Written: September 29, 2020
Abstract
This Essay illustrates how machine learning can disrupt legal scholarship through the algorithmic extraction and analysis of big data. Specifically, we utilize data from Harvard Law School’s Caselaw Access Project to model how courts tackle two thorny question in antitrust: the measure of market power and the balance between antitrust and regulation.
Keywords: machine learning, AI, big data, data modeling, Harvard Law School Caselaw Access Project, data analytics, antitrust, market power, regulation
JEL Classification: K21,K49
Suggested Citation: Suggested Citation
Felix Chang (Contact Author)
University of Cincinnati College of Law ( email )
P.O. Box 210040
Cincinnati, OH 45221-0040
United States
HOME PAGE: http://www.law.uc.edu/faculty-staff/felix-b-chang
