Jake M. Hofman

According to our database, Jake M. Hofman authored at least 31 papers between 2009 and 2023.

Collaborative distances:

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

2023

Pre-registration for Predictive Modeling.

Jake M. Hofman, Angelos Chatzimparmpas, Amit Sharma, Duncan J. Watts, Jessica Hullman

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

CoRR, 2023

Comparing scalable strategies for generating numerical perspectives.

Hancheng Cao, Sofia Eleni Spatharioti, Daniel G. Goldstein, Jake M. Hofman

CoRR, 2023

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

Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints.

Jamelle Watson-Daniels, Solon Barocas, Jake M. Hofman, Alexandra Chouldechova

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Investigating Perceptual Biases in Icon Arrays.

Cindy Xiong, Ali Sarvghad, Daniel G. Goldstein, Jake M. Hofman, Çagatay Demiralp

Proceedings of the CHI '22: CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April 2022, 2022

Round Numbers Can Sharpen Cognition.

Huy Anh Nguyen, Jake M. Hofman, Daniel G. Goldstein

Proceedings of the CHI '22: CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April 2022, 2022

Putting scientific results in perspective: Improving the communication of standardized effect sizes.

Yea-Seul Kim, Jake M. Hofman, Daniel G. Goldstein

Proceedings of the CHI '22: CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April 2022, 2022

2021

Datamations: Animated Explanations of Data Analysis Pipelines.

Xiaoying Pu, Sean Kross, Jake M. Hofman, Daniel G. Goldstein

Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Manipulating and Measuring Model Interpretability.

Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach

Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

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

Expanding the Scope of Reproducibility Research Through Data Analysis Replications.

Jake M. Hofman, Daniel G. Goldstein, Siddhartha Sen, Forough Poursabzi-Sangdeh

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

How Visualizing Inferential Uncertainty Can Mislead Readers About Treatment Effects in Scientific Results.

Jake M. Hofman, Daniel G. Goldstein, Jessica Hullman

Proceedings of the CHI '20: CHI Conference on Human Factors in Computing Systems, 2020

2018

To Put That in Perspective: Generating Analogies that Make Numbers Easier to Understand.

Christopher Riederer, Jake M. Hofman, Daniel G. Goldstein

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 2018

2017

What's Happening and What Happened: Searching the Social Web.

Omar Alonso, Vasileios Kandylas, Serge-Eric Tremblay, Jake M. Hofman, Siddhartha Sen

Proceedings of the 2017 ACM on Web Science Conference, 2017

2016

The Structural Virality of Online Diffusion.

Sharad Goel, Ashton Anderson, Jake M. Hofman, Duncan J. Watts

Manag. Sci., 2016

Split-door criterion for causal identification: Automatic search for natural experiments.

Amit Sharma, Jake M. Hofman, Duncan J. Watts

CoRR, 2016

Exploring Limits to Prediction in Complex Social Systems.

Travis Martin, Jake M. Hofman, Amit Sharma, Ashton Anderson, Duncan J. Watts

Proceedings of the 25th International Conference on World Wide Web, 2016

Improving Comprehension of Numbers in the News.

Pablo Javier Barrio, Daniel G. Goldstein, Jake M. Hofman

Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 2016

2015

Scalable Recommendation with Hierarchical Poisson Factorization.

Prem Gopalan, Jake M. Hofman, David M. Blei

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Estimating the Causal Impact of Recommendation Systems from Observational Data.

Amit Sharma, Jake M. Hofman, Duncan J. Watts

Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

2014

A large-scale exploration of group viewing patterns.

Allison June-Barlow Chaney, Mike Gartrell, Jake M. Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet

Proceedings of the ACM International Conference on Interactive Experiences for TV and Online Video, 2014

2013

Scalable Recommendation with Poisson Factorization.

Prem Gopalan, Jake M. Hofman, David M. Blei

CoRR, 2013

Sharding social networks.

Quang Duong, Sharad Goel, Jake M. Hofman, Sergei Vassilvitskii

Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013

2012

Who Does What on the Web: A Large-Scale Study of Browsing Behavior.

Sharad Goel, Jake M. Hofman, M. Irmak Sirer

Proceedings of the Sixth International Conference on Weblogs and Social Media, 2012

2011

Who says what to whom on twitter.

Shaomei Wu, Jake M. Hofman, Winter A. Mason, Duncan J. Watts

Proceedings of the 20th International Conference on World Wide Web, 2011

Everyone's an influencer: quantifying influence on twitter.

Eytan Bakshy, Jake M. Hofman, Winter A. Mason, Duncan J. Watts

Proceedings of the Forth International Conference on Web Search and Web Data Mining, 2011

2010

Predicting consumer behavior with Web search.

Sharad Goel, Jake M. Hofman, Sébastien Lahaie, David M. Pennock, Duncan J. Watts

Proc. Natl. Acad. Sci. USA, 2010

Graphical models for inferring single molecule dynamics.

Jonathan E. Bronson, Jake M. Hofman, Jingyi Fei, Ruben L. Gonzalez, Chris H. Wiggins

BMC Bioinform., 2010

Inferring relevant social networks from interpersonal communication.

Munmun De Choudhury, Winter A. Mason, Jake M. Hofman, Duncan J. Watts

Proceedings of the 19th International Conference on World Wide Web, 2010

2009

Characterizing individual communication patterns.

R. Dean Malmgren, Jake M. Hofman, Luís A. Nunes Amaral, Duncan J. Watts

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009