Tae Yano and Professor Dr. Noah A. Smith, both of Carnegie Mellon University Language Technologies Institute, and Professor Dr. John D. Wilkerson of the University of Washington Deaprtment of Political Science, presented a paper entitled Textual Predictors of Bill Survival in Congressional Committees, at New Directions in Analyzing Text as Data 2012, a conference held 5-6 October 2012 at the Harvard University Institute for Quantitative Social Science.
Here is the abstract:
A U.S. Congressional bill is a textual artifact that must pass through a series of hurdles to become a law. In this paper, we focus on one of the most precarious and least understood stages in a bill’s life: its consideration, behind closed doors, by a Congressional committee. We construct predictive models of whether a bill will survive committee, starting with a strong, novel baseline that uses features of the bill’s sponsor and the committee it is referred to. We augment the model with information from the contents of bills, comparing different hypotheses about how a committee decides a bill’s fate. These models give signiﬁcant reductions in prediction error and highlight the importance of bill substance in explanations of policy-making and agenda-setting.
A notable technology related to this research is the new probability-of-bill-passage feature on Dr. Joshua Tauberer’s GovTrack service.