Interdisciplinary Seminar in Quantitative Methods (ISQM): Arthur Spirling, PhD, New York University
October 25 @ 4:00 pm - 5:00 pm
3222 Angell Hall
Associate Professor, Politics, Data Science
‘Text Preprocessing for Unsupervised Learning: Why It Matters, When It Misleads, and What to Do about It’
ABSTRACT: Despite the popularity of unsupervised techniques for political science text-as-data research, the importance and implications of preprocessing decisions in this domain have received scant systematic attention. Yet, as we show, such decisions have profound effects on the results of real models for real data. We argue that substantive theory is typically too vague to be of use for feature selection, and that the supervised literature is not necessarily a helpful source of advice. To aid researchers working in unsupervised settings, we introduce a statistical procedure and software that examines the sensitivity of findings under alternate preprocessing regimes. This approach complements a researcher’s substantive understanding of a problem by providing a characterization of the variability changes in preprocessing choices may induce when analyzing a particular dataset. In making scholars aware of the degree to which their results are likely to be sensitive to their preprocessing decisions, it aids replication efforts.
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.
: Wed October 25, 4pm, ****LOCATION:
3222 Angell Hall*****
Angell Hall is connected to Haven Hall. If you go to the third floor of Haven Hall, you can follow a walking path to get the third floor of Angell Hall without ever leaving the building. See walking map here: https://hr.umich.edu/sites/default/files/m-h-t-a-halls.pdf