Jacob Montgomery

Professor Montgomery’s research focuses on how to use advanced computational methods for core social science tasks including measurement, theory testing, survey research, and causal inference. Substantively, his research focus is on American politics and (more recently) social media.

I am an Associate Professor and Director of Data Science Training in the Department of Political Science at Washington University in St. Louis. Starting in 2022, I am the Director of the Transdisciplinary Research Institute in Applied Data Science (TRIADS). I am also the chair of the political science track for the Division of Computational and Data Sciences and Director of The American Social Survey for the Weidenbaum Center on the Economy, Government, and Public Policy.

My research is in the areas of political methodology and American politics, with a special interest in measurement, Bayesian statistics/machine learning, and computational methods. My work has been published in many of the field’s leading journals—including the American Political Science Review, the American Journal of Political Science, Proceedings of the National Academy of Sciences, the Journal of Politics, and Political Analysis—and my work has received support from the National Science Foundation. In 2020, I was given the Emerging Scholar Award from The Society for Political Methodology, which honors a young researcher, within ten years of their degree, who is making notable contributions to the field.

My publications and working papers are listed here, and you can also access my curriculum vitae (linked above) and Google Scholar profile for additional information. I lead the (informal) Political Data Science Lab in the department.

My current projects include:

• Understanding the role of social media platforms in the political system including interventions to reduce belief in disinformation, platform regulation of political advertising, and populist rhetoric from political parties around the globe.
• Improving measurement of latent concepts like ideology of personality using advanced computational methods such as topic models, supervised machine learning for texts, gaussian process latent trait models, and active learning.

I graduated with a B.A. from Wake Forest University with majors in Political Science and Mathematical Economics. I earned an M.S. in Statistical Science as well as his Ph.D. (2011) in Political Science from Duke University.