1 code implementation • 12 Jan 2024 • Jacob M. Chen, Rohit Bhattacharya, Katherine A. Keith
Recent text-based causal methods attempt to mitigate confounding bias by including unstructured text data as proxies of confounding variables that are partially or imperfectly measured.
1 code implementation • 27 Jul 2023 • Katherine A. Keith, Sergey Feldman, David Jurgens, Jonathan Bragg, Rohit Bhattacharya
We contribute a new sampling algorithm, which we call RCT rejection sampling, and provide theoretical guarantees that causal identification holds in the observational data to allow for valid comparisons to the ground-truth RCT.
1 code implementation • 19 Dec 2022 • Li Lucy, Jesse Dodge, David Bamman, Katherine A. Keith
Scholarly text is often laden with jargon, or specialized language that can facilitate efficient in-group communication within fields but hinder understanding for out-groups.
no code implementations • EMNLP (CINLP) 2021 • Katherine A. Keith, Douglas Rice, Brendan O'Connor
Using observed language to understand interpersonal interactions is important in high-stakes decision making.
1 code implementation • 2 Sep 2021 • Amir Feder, Katherine A. Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E. Roberts, Brandon M. Stewart, Victor Veitch, Diyi Yang
A fundamental goal of scientific research is to learn about causal relationships.
1 code implementation • Findings (ACL) 2021 • Andrew Halterman, Katherine A. Keith, Sheikh Muhammad Sarwar, Brendan O'Connor
Automated event extraction in social science applications often requires corpus-level evaluations: for example, aggregating text predictions across metadata and unbiased estimates of recall.
no code implementations • EMNLP (NLP+CSS) 2020 • Katherine A. Keith, Christoph Teichmann, Brendan O'Connor, Edgar Meij
We find for this application (1) some annotator disagreements of economic policy uncertainty can be attributed to ambiguity in language, and (2) switching measurements from keyword-matching to supervised machine learning classifiers results in low correlation, a concerning implication for the validity of the index.
no code implementations • ACL 2020 • Katherine A. Keith, David Jensen, Brendan O'Connor
For example, an individual's entire history of social media posts or the content of a news article could provide a rich measurement of multiple confounders.
no code implementations • 7 Jun 2019 • Katherine A. Keith, Amanda Stent
Every fiscal quarter, companies hold earnings calls in which company executives respond to questions from analysts.
1 code implementation • NAACL 2018 • Katherine A. Keith, Su Lin Blodgett, Brendan O'Connor
Dependency parsing research, which has made significant gains in recent years, typically focuses on improving the accuracy of single-tree predictions.
no code implementations • EMNLP 2017 • Katherine A. Keith, Abram Handler, Michael Pinkham, Cara Magliozzi, Joshua McDuffie, Brendan O'Connor
We propose a new, socially-impactful task for natural language processing: from a news corpus, extract names of persons who have been killed by police.