Justin Grimmer

Associate Professor of Political Science and the College; Executive Committee Member, Masters in Computational Social Science Program

Dr. Grimmer is an associate professor of political science and the College. At UChicago since the fall of 2017, his research examines how representation occurs in American politics using new statistical methods. His first book Representational Style in Congress: What Legislators Say and Why It Matters (Cambridge University Press, 2013) shows how senators define the type of representation they provide constituents and how this affects constituents' evaluations and won the Fenno Prize from the legislative studies section.  

His second book The Impression of Influence: How Legislator Communication and Government Spending Cultivate a Personal Vote (Princeton University Press, with Sean J. Westwood and Solomon Messing) demonstrates how legislators ensure they receive credit for government actions.  His work has appeared in the American Political Science ReviewAmerican Journal of Political ScienceJournal of PoliticsPolitical AnalysisProceedings of the National Academy of Sciences, Regulation and Governance, and other journals. 

Select Publications

Discovery of Treatments from Text Corpora (with Christian Fong) Forthcoming In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2016) Berlin, Germany​

Money in Exile: Campaign Contributions and Committee Access (with Eleanor Neff Powell) Forthcoming, Journal of Politics Supplemental Appendix

Measuring Representational Style in the House: The Tea Party, Obama and Legislators' Changing Expressed Priorities in Data Analytics in Social Science, Government, and Industry Edited Volume from Cambridge University Press2016.   

We're All Social Scientists Now: How Big Data, Machine Learning, and Causal Inference Work Together PS: Political Science & Politics, 2015. 48(1), 80-83

Congressmen in Exile: The Politics and Consequences of Involuntary Committee Removal (with Eleanor Neff Powell) The Journal of Politics, 2013. 75(4), 907-920.  Supplementary Information

Appropriators Not Position Takers: The Distorting Effects of Electoral Incentives on Congressional Representation American Journal of Political Science, 2013.  57 (3), 624-642 Supplementary Information

Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts (with Brandon Stewart) Political Analysis, 2013. 21 (3), 267--297

Elevated Threat-Levels and Decreased Expectations: How Democracy Handles Terrorist Threats (with Tabitha Bonilla) Poetics, 2013. 41, 650--669 (Special Issue on Topic Models in Social Science) 

Evaluating Model Performance in Fictitious Prediction Problems.  Discussion of ``Multinomial Inverse Regression for Text Analysis" by Matthew Taddy.  Journal of the American Statistical Association, 2013.108 (503) 770-771

How Words and Money Cultivate a Personal Vote: The Effect of Legislator Credit Claiming on Constituent Credit Allocation (with Solomon Messing and Sean Westwood) American Political Science Review, 2012. 106 (4), 703-719. Supplementary Information

General Purpose Computer-Assisted Clustering and Conceptualization (With Gary King)  Proceedings of the National Academy of Sciences, 2011.  108(7), 2643-2650.

An Introduction to Bayesian Inference via Variational Approximations Political Analysis, 2011. 19 (1) 32-47 Supplemental Notes

Approval Regulation and Endogenous Provision of Confidence: Theory and Analogies to Licensing, Safety, and Financial Regulation (with Dan Carpenter and Eric Lomazoff)  Regulation and Governance, 2010. 4(4) 383-407

A Bayesian Hierarchical Topic Model for Political Texts: Measuring Expressed Agendas in Senate Press Releases Political Analysis, 2010. 18(1) 1-35.