Brandon M. Stewart

According to our database, Brandon M. Stewart authored at least 19 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

AutoPersuade: A Framework for Evaluating and Explaining Persuasive Arguments.

Till Saenger, Musashi Hinck, Justin Grimmer, Brandon M. Stewart

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

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

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

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., January, 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

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, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan

CoRR, 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

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GPT Deciphering Fedspeak: Quantifying Dissent Among Hawks and Doves.

Denis Peskoff, Adam Visokay, Sander Schulhoff, Benjamin Wachspress, Alan Blinder, Brandon M. Stewart

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Credible without Credit: Domain Experts Assess Generative Language Models.

Denis Peskoff, Brandon M. Stewart

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

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, Diyi Yang

Trans. Assoc. Comput. Linguistics, 2022

2018

How to Make Causal Inferences Using Texts.

Naoki Egami, Christian J. Fong, Justin Grimmer, Margaret E. Roberts, Brandon M. Stewart

CoRR, 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 algorithmic confounding in recommendation systems increases homogeneity and decreases utility.

Allison June-Barlow Chaney, Brandon M. Stewart, Barbara E. Engelhardt

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

2017

Discourse: MOOC Discussion Forum Analysis at Scale.

Alexander Kindel, Michael Yeomans, Justin Reich, Brandon M. Stewart, Dustin Tingley

Proceedings of the Fourth ACM Conference on Learning @ Scale, 2017

2016

The Civic Mission of MOOCs: Measuring Engagement across Political Differences in Forums.

Justin Reich, Brandon M. Stewart, Kimia Mavon, Dustin Tingley

Proceedings of the Third ACM Conference on Learning @ Scale, 2016

Navigating the Local Modes of Big Data: The Case of Topic Models.

Margaret E. Roberts, Brandon M. Stewart, Dustin Tingley

Proceedings of the Computational Social Science: Discovery and Prediction, 2016

2015

TopicCheck: Interactive Alignment for Assessing Topic Model Stability.

Jason Chuang, Margaret E. Roberts, Brandon M. Stewart, Rebecca Weiss, Dustin Tingley, Justin Grimmer, Jeffrey Heer

Proceedings of the NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31, 2015

2014

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., November, 2014

2013

Learning to Extract International Relations from Political Context.

Brendan O'Connor, Brandon M. Stewart, Noah A. Smith

Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, 2013