Political event data – categorical data on who did what to whom – is now being coded in near real time using open source software. This talk will look at some of the data sets that have recently become available, then consider the practical issues involved in doing customized coding, with a focus on the TABARI coding system and other tools developed at Penn State. Topics will include text filtering and formatting, named-entity recognition, the TABARI verb phrase and noun phrase dictionaries, and the CAMEO event and actor coding schemes. The talk assumes a general familiarity with social science data but otherwise has no prerequisites. Background information on the Penn State event data project can be found at http://eventdata.psu.edu.
Dr. Schrodt is Professor of Political Science at Pennsylvania State University. He received an M.A. in mathematics and a Ph.D. in political science from Indiana University. Prior to coming to Penn State in 2010, he taught for 21 years at the University of Kansas and 11 years at Northwestern University, where he helped develop Northwestern's programs on mathematical methods in the social sciences. Dr. Schrodt's major areas of research are quantitative models of political conflict and computational political methodology. His current research focuses on predicting political change using statistical and pattern recognition methods, research that has been supported by the National Science Foundation, the Defense Advanced Research Projects Agency, and the U.S. government's multi-agency Political Instability Task Force.