AbstractsPolitical Science

Political polarization is a common topic in the news and media, but not much has been done to understand the distribution of the preferences of the U.S. voting population. Political scientists have drawn different conclusions on the current state of political polarization within the U.S. voting population based on survey data and basic spatial voting models. In this work, I present a spatial voting model that analyzes voting data at a more fine-grained level in order to use Bayesian techniques to infer the underlying distribution of political preferences of the population. Further, I verify these results by comparing it to alternative public opinion measurements and measuring the accuracy in completing prediction tasks. This work adds a new perspective to the current discussion within the political science community of the recent trends of political polarization.