Measuring Swing Voters with a Machine Learning Approach

Date
-
Event Sponsor
The Munro Lectureship Fund and The Lane Center
Location
Encina Hall West, Room 400 (GSL)
Speaker

Chris Hare, Assistant Professor of Political Science, University of California, Davis

 

Abstract

In this paper, we use a nonparametric machine learning method (boosted decision trees) to derive a more valid and finely-grained measure of swing voter propensity and identify characteristics of swing voters. As past work has demonstrated, boosted trees excel in their discovery of complex interactions and nonlinearities present in the relationship between response and predictor variables. This makes boosted trees a promising candidate for identifying niche subgroups of swing voters, and modeling how swing voter characteristics and behavior varies across subgroups. We use this approach to analyze three-wave panel data from the 2012 Cooperative Campaign Analysis Project. The boosting model generates individual predictions that outperform existing measures of swing voters. It also uncovers a range of meaningful two, three, and even four-way interaction effects that can be used to assess how the influence of ideological moderation and cross-pressures on swing voting vary across groups of voters.

 

Biography
I am an assistant professor of political science at the University of California, Davis. I received my PhD in political science from the University of Georgia and my BA and MA in political science from the University of Southern Mississippi.
 
My research agenda encompasses ideology and voting behavior in the mass public, campaign strategy, politics and religion, and political polarization. Methodologically, I am interested in measurement theory and ideal point estimation, Bayesian methods, and applying machine learning to model political behavior.
 
I am currently working on a series of projects involving the measurement of issue salience to voters and the use of scaling methods to analyze the structure of ideology in the American electorate. 
 
I have also worked as a pro bono consultant on data anlytics projects for conservative, Republican candidates and groups, including CARLY for America.