Arthur Spirling, Ph.D.
Associate Professor, Politics, Data Science
New York University
‘Text Preprocessing for Unsupervised Learning: Why It Matters, When It Misleads, and What to Do about It’
BIO: Arthur Spirling is an Associate Professor of Politics and Data Science at New York University. He is the Deputy Director and the Director of Graduate Studies at the Center for Data Science, and Chair of the Education and Training Working Group of the Moore-Sloan Data Science Environment. He specializes in political methodology and legislative behavior, with an interest in the application of texts-as-data, Bayesian statistics, item response theory and generalized linear models in political science. His substantive field is comparative politics, and he focuses primarily on the United Kingdom. He received his PhD from the University of Rochester, Department of Political Science, in 2008. From 2008 to 2015, he was an Assistant Professor and then the John L. Loeb Associate Professor of the Social Sciences in the Department of Government at Harvard University.