Learning to Extract International Relations from Political Context. - Brendan O'Connor 001; Brandon M. Stewart; Noah A. Smith (ACL (1), 2013)

Computer-Assisted Reading and Discovery for Student Generated Text in Massive Open Online Courses. - Justin Reich; Dustin Tingley; Jetson Leder-Luis; Margaret E. Roberts; Brandon M. Stewart (J. Learn. Anal., 2014)

TopicCheck: Interactive Alignment for Assessing Topic Model Stability. - Jason Chuang; Margaret E. Roberts; Brandon M. Stewart; Rebecca Weiss; Dustin Tingley; Justin Grimmer; Jeffrey Heer (HLT-NAACL, 2015)

Navigating the Local Modes of Big Data: The Case of Topic Models. - Margaret E. Roberts; Brandon M. Stewart; Dustin Tingley (Computational Social Science, 2016)

The Civic Mission of MOOCs: Measuring Engagement across Political Differences in Forums. - Justin Reich; Brandon M. Stewart; Kimia Mavon; Dustin Tingley (L@S, 2016)

Discourse: MOOC Discussion Forum Analysis at Scale. - Alexander Kindel; Michael Yeomans; Justin Reich; Brandon M. Stewart; Dustin Tingley (L@S, 2017)

How algorithmic confounding in recommendation systems increases homogeneity and decreases utility. - Allison June-Barlow Chaney; Brandon M. Stewart; Barbara E. Engelhardt (RecSys, 2018)

The Civic Mission of MOOCs: Engagement across Political Differences in Online Forums. - Michael Yeomans; Brandon M. Stewart; Kimia Mavon; Alexander Kindel; Dustin Tingley; Justin Reich (Int. J. Artif. Intell. Educ., 2018)

How to Make Causal Inferences Using Texts. - Naoki Egami; Christian J. Fong; Justin Grimmer; Margaret E. Roberts; Brandon M. Stewart (CoRR, 2018)

Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond. - 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; et al. (Trans. Assoc. Comput. Linguistics, 2022)

Credible without Credit: Domain Experts Assess Generative Language Models. - Denis Peskoff; Brandon M. Stewart (ACL (2), 2023)

GPT Deciphering Fedspeak: Quantifying Dissent Among Hawks and Doves. - Denis Peskoff; Adam Visokay; Sander Schulhoff; Benjamin Wachspress; Alan Blinder; Brandon M. Stewart (EMNLP (Findings), 2023)

Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models. - Naoki Egami; Musashi Hinck; Brandon M. Stewart; Hanying Wei (NeurIPS, 2023)

Using Large Language Model Annotations for Valid Downstream Statistical Inference in Social Science: Design-Based Semi-Supervised Learning. - Naoki Egami; Musashi Jacobs-Harukawa; Brandon M. Stewart; Hanying Wei (CoRR, 2023)

REFORMS: Reporting Standards for Machine Learning Based Science. - Sayash Kapoor; Emily Cantrell; Kenny Peng; Thanh Hien Pham; Christopher A. Bail; Odd Erik Gundersen; Jake M. Hofman; Jessica Hullman; Michael A. Lones; Momin M. Malik; Priyanka Nanayakkara; Russell A. Poldrack; et al. (CoRR, 2023)

Naive regression requires weaker assumptions than factor models to adjust for multiple cause confounding. - Justin Grimmer; Dean Knox; Brandon M. Stewart (J. Mach. Learn. Res., 2023)

Manipulative tactics are the norm in political emails: Evidence from 300K emails from the 2020 US election cycle. - Arunesh Mathur; Angelina Wang; Carsten Schwemmer; Maia Hamin; Brandon M. Stewart; Arvind Narayanan (Big Data Soc., 2023)

More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play. - Wichayaporn Wongkamjan; Feng Gu; Yanze Wang; Ulf Hermjakob; Jonathan May; Brandon M. Stewart; Jonathan K. Kummerfeld; Denis Peskoff; Jordan L. Boyd-Graber (ACL (1), 2024)

AutoPersuade: A Framework for Evaluating and Explaining Persuasive Arguments. - Till Saenger; Musashi Hinck; Justin Grimmer; Brandon M. Stewart (EMNLP, 2024)