Our 24th workshop features a conversation with Michelle Torres on “Benevolent Billionaires? Evaluating the Influence of Wealthy Owners on Local News” on March 12, 2024, from 9:00AM – 10:30AM PT.
The Hoover Institution Workshop on Using Text as Data in Policy Analysis showcases applications of natural language processing, structured human readings, and machine learning methods to analyze text as data for examining policy issues in economics, history, national security, political science, and other fields. Steven J. Davis and Justin Grimmer organize the workshop.
ABOUT THE SPEAKERS
Michelle Torres is an Assistant Professor in the Department of Political Science at the University of California, Los Angeles. She holds a Ph.D. in Political Science and a A.M. in Statistics from Washington University in St. Louis. Her broad research interests are in the fields of political methodology and political behavior, with a special interest in computational methods for unstructured data, causal inference, public opinion, and political communication. Michelle's current research focuses on political methodology and the ways in which we can make statistical and computer science methods accessible to political science. Michelle is also interested in understanding the factors that impact the generation of verbal and visual content used to communicate political events, as well as in the impact that these have on attitude and opinion formation.
Steven J. Davis is the Thomas W. and Susan B. Ford Senior Fellow at the Hoover Institution and Senior Fellow at the Stanford Institute for Economic Policy Research. He studies business dynamics, labor markets, and public policy. He advises the U.S. Congressional Budget Office and the Federal Reserve Bank of Atlanta, co-organizes the Asian Monetary Policy Forum and is co-creator of the Economic Policy Uncertainty Indices, the Survey of Business Uncertainty, and the Survey of Working Arrangements and Attitudes. Davis hosts “Economics, Applied,” a podcast series sponsored by the Hoover Institution.
Justin Grimmer is a senior fellow at the Hoover Institution and a professor in the Department of Political Science at Stanford University. His current research focuses on American political institutions, elections, and developing new machine-learning methods for the study of politics.
