Discovering significant topics from legal decisions with selective inference

• 主要作者: SOH, Jerrold Tsin Howe
• 格式: text
• 語言: English
• 出版: Institutional Knowledge at Singapore Management University 2024
• 主題: domain name disputes; European Court of Human Rights; legal language processing; text-as-data; topic models; Courts; Legal Studies; Numerical Analysis and Scientific Computing
• 在線閱讀: https://ink.library.smu.edu.sg/sol_research/4433; https://ink.library.smu.edu.sg/context/sol_research/article/6391/viewcontent/Discovering_significant_topics_from_legal_decisions_with_selective_inference_pvoa_cc_by.pdf
• 機構: Singapore Management University

We propose and evaluate an automated pipeline for discovering significant topics from legal decision texts by passing features synthesized with topic models through penalized regressions and post-selection significance tests. The method identifies case topics significantly correlated with outcomes,...