A combinatorial prediction market for the U.S. elections. - Miroslav Dudík; Sébastien Lahaie; David M. Pennock; David M. Rothschild (EC, 2013)

The extent of price misalignment in prediction markets. - David M. Rothschild; David M. Pennock (Algorithmic Finance, 2014)

Evaluating the scale, growth, and origins of right-wing echo chambers on YouTube. - Homa Hosseinmardi; Amir Ghasemian; Aaron Clauset; David M. Rothschild; Markus Mobius; Duncan J. Watts (CoRR, 2020)

Log-time Prediction Markets for Interval Securities. - Miroslav Dudík; Xintong Wang 002; David M. Pennock; David M. Rothschild (AAMAS, 2021)

Towards a Theory of Confidence in Market-Based Predictions. - Rupert Freeman; David M. Pennock; Daniel M. Reeves; David M. Rothschild; Bo Waggoner (ISIPTA, 2021)

Designing a Combinatorial Financial Options Market. - Xintong Wang 002; David M. Pennock; Nikhil R. Devanur; David M. Rothschild; Biaoshuai Tao; Michael P. Wellman (EC, 2021)

Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment. - Sofia Eleni Spatharioti; David M. Rothschild; Daniel G. Goldstein; Jake M. Hofman (CoRR, 2023)

The science of fake news. - David M. J. Lazer; Matthew A. Baum; Yochai Benkler; Adam J. Berinsky; Kelly M. Greenhill; Filippo Menczer; Miriam J. Metzger; Brendan Nyhan; Gordon Pennycook; David M. Rothschild; Michael Schudson; Steven A. Sloman; et al. (CoRR, 2023)

The diminishing state of shared reality on US television news. - Homa Hosseinmardi; Samuel Wolken; David M. Rothschild; Duncan J. Watts (CoRR, 2023)

Designing Expressive and Liquid Financial Options Markets via Linear Programming and Automated Market Making. - Xintong Wang 002; David M. Pennock; David M. Rothschild; Nikhil R. Devanur (ICAIF, 2024)

Math Education With Large Language Models: Peril or Promise? - Harsh Kumar; David M. Rothschild; Daniel G. Goldstein; Jake M. Hofman (AIED (4), 2025)

Effects of LLM-based Search on Decision Making: Speed, Accuracy, and Overreliance. - Sofia Eleni Spatharioti; David M. Rothschild; Daniel G. Goldstein; Jake M. Hofman (CHI, 2025)

Media Bias Detector: Designing and Implementing a Tool for Real-Time Selection and Framing Bias Analysis in News Coverage. - Jenny S. Wang; Samar Haider; Amir Tohidi; Anushkaa Gupta; Yuxuan Zhang; Chris Callison-Burch; David M. Rothschild; Duncan J. Watts (CHI, 2025)

Prevalence and Prevention of Large Language Model Use in Crowd Work. - Veniamin Veselovsky; Manoel Horta Ribeiro; Philip Cozzolino; Andrew Gordon; David M. Rothschild; Robert West 001 (Commun. ACM, 2025)

The Agentic Economy. - David M. Rothschild; Markus Mobius; Jake M. Hofman; Eleanor Wiske Dillon; Daniel G. Goldstein; Nicole Immorlica; Sonia Jaffe; Brendan Lucier; Aleksandrs Slivkins; Matthew Vogel (CoRR, 2025)

Bringing Everyone to the Table: An Experimental Study of LLM-Facilitated Group Decision Making. - Mohammed Alsobay; David M. Rothschild; Jake M. Hofman; Daniel G. Goldstein (CoRR, 2025)