| Autor: |
Zhaowei Ren, Felix B. Chang, James T. Lee, Joshua Beckelhimer, Erin E. McCabe |
| Rok vydání: |
2021 |
| Zdroj: |
Stanford Journal of Computational Antitrust. :117-131 |
| Popis: |
Utilizing antitrust decisions extracted from the Caselaw Access Project, we aggregate—or embed—layers of topic modeling into a single set of visualizations. Aggregated models can provide new perspectives on how courts tackle thorny doctrinal questions, such as the measure of market power and the balance between antitrust and regulation. Our central contribution is the improvement of natural language processing to provide greater context for key terms. Our secondary contribution is a new suite of tools to assess the weighty policy arguments that currently dominate antitrust. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
