An Introduction to Analyzing Political Texts

Join Arthur Spirling for a workshop on analyzing political texts.
He is Professor of Politics and Data Science at New York University. He is the Deputy Director and the Director of Graduate Studies (MSDS) at the Center for Data Science, and Chair of the Executive Committee of the Moore-Sloan Data Science Environment.
He specializes in political methodology and legislative behavior, with an interest in the application of text-as-data/NLP, Bayesian statistics, machine learning, 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 is especially interested in British Political Development for the period after the Great Reform Act.
He is the faculty coordinator for the NYU Text-as-Data speaker series.