Document Type
Article
Publication Date
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.
Recommended Citation
Chang, Felix B.; McCabe, Erin; and Lee, James, "Mining the Harvard Caselaw Access Project" (2020). Faculty Articles and Other Publications. 382.
https://scholarship.law.uc.edu/fac_pubs/382