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Elliott Ash Profile picture
Elliott Ash
@ellliottt
Prof @ETH Zurich: Law, Economics, and Data Science; @cepr_org affiliate (PE). Previously @warwickecon, @PrincetonSPIA, @columbia_econ, @ColumbiaLaw, @UTAustin.
May 19, 2023 • 6 tweets • 4 min read
Q: Give an example NLP task where transformers don't give the best performance. A: Extractive summarization on legal documents!

Just posted: "Legal Extractive Summarization of U.S. Court Opinions":
arxiv.org/abs/2305.08428
(with E. Bauer, @dominsta_nlp & N. Gu, all of @ETH_en)

Repo: github.com/bauerem/legal_…

Web demo: huggingface.co/spaces/bauerem… ImageImageImage
May 18, 2023 • 16 tweets • 16 min read
Recently posted at @cepr_org: "Text Algorithms in Economics" with @StephenEKHansen (forthcoming in ARE @AnnualReviews).

Ungated version: elliottash.com/wp-content/upl…

Companion code notebooks: github.com/sekhansen/text…

& now a 🧵 on the highlights... Image Methods covered in the "Text Algorithms" section:
1) preliminaries/ pre-processing
2) bag-of-words representation of docs
3) dimensionality reduction, e.g. topic models
4) word embeddings with local context
5) embedding sequences with attention
6) supervised learning Image
Aug 15, 2021 • 15 tweets • 12 min read
A short thread introducing new work with @PinchOfData and @phinifa:

“Text Semantics Capture Political and Economic Narratives”

Paper: arxiv.org/abs/2108.01720
Repo: github.com/relatio-nlp/re…
Demo: colab.research.google.com/drive/1Zychi2O… Human beings are storytellers.

It’s no wonder then that social scientists are increasingly interested in narratives -- the stories we tell in fiction, politics, and life -- and how they shape beliefs, behavior, and government policies.

e.g. @RobertJShiller
Feb 7, 2021 • 11 tweets • 7 min read
“In politics, when reason and emotion collide, emotion invariably wins.” -- Drew Westen, The Political Brain.

Interesting idea! What do the data say about that?

New working paper: "Emotion and Reason in Political Language", with @gloriagennaro.

PDF: bit.ly/gennaro-ash-em… We use computational linguistics tools ("word embeddings") to map out a dimension for emotion on one pole and cognition on another pole.