Bayesian change point analysis for polling data

After an election campaign, it is important to identify events that marked change points in voter support. Pre-election polls provide a measure of the state of voter support at points in time during the election campaign. However, polling data is difficult to analyze because it is sparse and comes from multiple sources, which can be individually biased. In this paper, we propose a change point model for polling data that increases confidence by combining polls and identifying change points simultaneously. We demonstrate the utility of our model on polling data from the 2008 U.S. presidential election.