Honesty in an Online Labor Market. - Siddharth Suri; Daniel G. Goldstein; Winter A. Mason (Human Computation, 2011)

The effects of exposure time on memory of display advertisements. - Daniel G. Goldstein; R. Preston McAfee; Siddharth Suri (EC, 2011)

The structure of online diffusion networks. - Sharad Goel; Duncan J. Watts; Daniel G. Goldstein (EC, 2012)

The wisdom of smaller, smarter crowds. - Daniel G. Goldstein; Randolph Preston McAfee; Siddharth Suri (EC, 2014)

Predicting Individual Behavior with Social Networks. - Sharad Goel; Daniel G. Goldstein (Mark. Sci., 2014)

The cost of annoying ads. - Daniel G. Goldstein; R. Preston McAfee; Siddharth Suri (SIGecom Exch., 2014)

Improving the Effectiveness of Time-Based Display Advertising. - Daniel G. Goldstein; R. Preston McAfee; Siddharth Suri (ACM Trans. Economics and Comput., 2015)

Improving Comprehension of Numbers in the News. - Pablo Javier Barrio; Daniel G. Goldstein; Jake M. Hofman (CHI, 2016)

Subjective beliefs about the income distribution and preferences for redistribution. - Lionel Page; Daniel G. Goldstein (Soc. Choice Welf., 2016)

Erratum to: The role of subjective beliefs in preferences for redistribution. - Lionel Page; Daniel G. Goldstein (Soc. Choice Welf., 2016)

VoxPL: Programming with the Wisdom of the Crowd. - Daniel W. Barowy; Emery D. Berger; Daniel G. Goldstein; Siddharth Suri (CHI, 2017)

Learning in the Repeated Secretary Problem. - Daniel G. Goldstein; R. Preston McAfee; Siddharth Suri; James R. Wright (EC, 2017)

To Put That in Perspective: Generating Analogies that Make Numbers Easier to Understand. - Christopher Riederer; Jake M. Hofman; Daniel G. Goldstein (CHI, 2018)

How Visualizing Inferential Uncertainty Can Mislead Readers About Treatment Effects in Scientific Results. - Jake M. Hofman; Daniel G. Goldstein; Jessica Hullman (CHI, 2020)

Expanding the Scope of Reproducibility Research Through Data Analysis Replications. - Jake M. Hofman; Daniel G. Goldstein; Siddhartha Sen 001; Forough Poursabzi-Sangdeh (WWW (Companion Volume), 2020)

How good is good enough for COVID19 apps? The influence of benefits, accuracy, and privacy on willingness to adopt. - Gabriel Kaptchuk; Daniel G. Goldstein; Eszter Hargittai; Jake M. Hofman; Elissa M. Redmiles (CoRR, 2020)

Learning When to Stop Searching. - Daniel G. Goldstein; R. Preston McAfee; Siddharth Suri; James R. Wright (Manag. Sci., 2020)

Manipulating and Measuring Model Interpretability. - Forough Poursabzi-Sangdeh; Daniel G. Goldstein; Jake M. Hofman; Jennifer Wortman Vaughan; Hanna M. Wallach (CHI, 2021)

Datamations: Animated Explanations of Data Analysis Pipelines. - Xiaoying Pu; Sean Kross; Jake M. Hofman; Daniel G. Goldstein (CHI, 2021)

Putting scientific results in perspective: Improving the communication of standardized effect sizes. - Yea-Seul Kim; Jake M. Hofman; Daniel G. Goldstein (CHI, 2022)

Round Numbers Can Sharpen Cognition. - Huy Anh Nguyen; Jake M. Hofman; Daniel G. Goldstein (CHI, 2022)

Investigating Perceptual Biases in Icon Arrays. - Cindy Xiong; Ali Sarvghad; Daniel G. Goldstein; Jake M. Hofman; Çagatay Demiralp (CHI, 2022)

How Good is Good Enough? Quantifying the Impact of Benefits, Accuracy, and Privacy on Willingness to Adopt COVID-19 Decision Aids. - Gabriel Kaptchuk; Daniel G. Goldstein; Eszter Hargittai; Jake M. Hofman; Elissa M. Redmiles (DTRAP, 2022)

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)

Comparing scalable strategies for generating numerical perspectives. - Hancheng Cao; Sofia Eleni Spatharioti; Daniel G. Goldstein; Jake M. Hofman (CoRR, 2023)

Using Open Data to Automatically Generate Localized Analogies. - Sofia Eleni Spatharioti; Daniel G. Goldstein; Jake M. Hofman (CHI, 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)

Learning not cheating: AI assistance can enhance rather than hinder skill development. - Benjamin Lira; Todd Rogers; Daniel G. Goldstein; Lyle H. Ungar; Angela Lee Duckworth (CoRR, 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)