Poster #131 - To vote or not to vote: Partisanship and political participation as predictors of voting

• In Event: Saturday Poster Luncheon

Abstract

This study investigates the predictors of voting behavior in the United States, with particular emphasis on political participation (online and offline), political identity salience, and partisanship. Amidst a rapidly evolving political landscape influenced by digital media and shifting civic norms, the research aims to clarify how different forms of political engagement shape individuals' voting decisions. The study draws on data from the 2022 Cooperative Election Study (CES), a stratified, nationally representative survey conducted in two waves around the midterm elections. Utilizing structural equation modeling (SEM) and logistic regression, the research tests direct and mediated relationships among political engagement variables, controlling for demographic factors such as age, income, race, and education. Our results show that online political participation and political identity salience significantly predict voting behavior. Individuals with higher levels of online engagement and stronger identification with their political party are more likely to vote in midterm elections. We also find that online political participation influences voting and significantly predicts offline political participation. The study expands the understanding of how digital modes of political participation may now rival or surpass traditional engagement in influencing electoral outcomes. The findings from this study challenge longstanding assumptions about the primacy of offline political participation in mobilizing voters and call attention to the role of emerging digital tools in democratic engagement. These findings have implications for political campaigns and policy efforts to increase voter turnout.

Author

• Ojooluwa Ibiloye, University of Delaware
  Presenting Author