Elliott Ash

text_econ_2022. Materials for PhD course on text data in economics

nlp_lss_2023. repo for "Natural Language Processing for Law and Social Science" @ ETH Zurich, Spring 2022

lm_lss_2024. Materials for "Language Models for Law and Social Science" (ETH Zurich), Spring 2024

text_ml_course_2018. Slides and jupter notebooks for course on text analysis and machine learning for social science

emotionmeter. Python code for producing emotionality scores from Gennaro and Ash (2021).

robot_judge_2020. Slides and code examples for Autumn 2020 Course at ETH Zurich, "Building a Robot Judge: Data Science for Decision-Making."

robot_judge_2023. Materials for "Building a Robot Judge: Data Science for Decision-Making" (ETH Zurich), Autumn 2023

nlp_lss_2022. 2022 version of Natural Language Processing for Low and Social Science, taught at ETH Zurich

legal_dna_2020. Course materials for "Sequencing Legal DNA: NLP for Law and Political Economy", to be taught at ETH February-May 2020

robot_judge_2021. Jupyter Notebook

legal_dna_2021. Course materials for Spring 2021 ETH Course, "Sequencing Legal DNA: NLP for Law and Political Economy"

lm_lss_2025. Materials for "Language Models for Law and Social Science" (ETH Zurich), Spring 2025

robot_judge_2019. Course materials for "Building a Robot Judge: Data Science for the Law", Spring 2019

big_data_policy_2020. Course materials for "Big Data for Public Policy", ETH Zurich Spring 2020

robot_judge_2022. Materials for "Building a Robot Judge: Data Science for Decision-Making", Autumn 2022

tad-2026. Materials for "Text as Data" Course (2026)

tax-classification. Classification of tax related and source on state session laws

stataconda. an open-source IDE that runs both stata and python code.

labor-contracts. Python

nlp_econ_recipes. A set of recipes and FAQs for text anaysis in economics and other social sciences.

ocr_pdfs. Scripts for OCR

rtalk. Stata

AutomatingAbercrombie. Replication code for "Automating Abercrobie: Machine-learning Trademark Distinctiveness" by Adarsh, Ash, Bechtold, Beebe, & Fromer, Journal of Empirical Legal Studies (2024).