The Paradox of Persuasion: Interpersonal Influence in Everyday Conversation
Political scientists have been using individuals’ self-reported efforts to try to influence the votes of others as one indicator of political activism for more than a half-century. However, in spite of this widespread use, very little is known about the motivations of interpersonal persuasion. This dissertation examines why some individuals try to influence the votes of others during the course of their everyday political conversations, while others are content to discuss politics without trying to persuade. Although attempts to persuade are often treated as a form of campaign participation with a goal of influencing the outcome of the election, I find that the motivations for persuasion are more internal and interpersonal than the motivations of other forms of campaign involvement. I argue that interpersonal persuasion should be treated as a form of discursive participation, with consequences for our understanding of public opinion and deliberation.
Argyle, Lisa, Marcus Arrajj, Skylar Covich, Egidio Garay, Julian Gottleib, Heather Hodges, and Eric Smith. 2016. “Economic Performance and Presidential Trait Evaluations: A Longitudinal Analysis.” Electoral Studies 43(3): 52 - 62.
*Featured on the Presidential Powers blog.
Han, Hahrie, with support from Lisa Argyle. April 2016. “A Program Review of the Promoting Electoral Reform and Democratic Participation (PERDP) Initiative of the Ford Foundation.” Ford Foundation. (Link to PDF)
Cowell-Meyers, Kimberly and Lisa Argyle. 2015. “2015 APSA Teaching and Learning Conference and Track Summaries: Curricular and Program Assessment.” PS: Political Science and Politics 48(3): 501 – 503.
Works in Progress:
“Why Do Voters Try to Persuade Each Other? An Evaluation of the Motivations of Interpersonal Persuasion.”
Using data from the 2008 National Annenberg Election Studies Phone Survey, I compare the determinants of political persuasion with other forms of campaign participation. I find that individuals’ attempts to persuade others are driven more by internal efficacy and social norms than by external efficacy or the campaign environment. I conclude that persuasion is better understood as a form of discursive participation than as an instrumental campaign behavior.
“(Machine) Learning about Interpersonal Political Persuasion.”
I argue that attempts at interpersonal political persuasion are a unique form of political behavior that should not be automatically scaled with other forms of campaign participation. I test this argument by comparing political persuasion to two other sets of behaviors: campaign participation (displaying a sign/bumper sticker, donating money, volunteering, or attending a campaign meeting/rally), and discursive participation (talking about politics, attending a community problem-solving meeting, sharing political information online). Using factor analysis and two machine learning approaches (random forest and lasso) on data from the 2012 ANES, I find that political persuasion has more in common with other forms of discursive participation than it does with campaign participation. Furthermore, I use the example of a prominent debate about polarization in the American public (Abramowitz 2010; Fiorina and Abrams 2009) to demonstrate the substantive implications of correctly understanding the nature of interpersonal persuasive behavior.
“Is the Public Polarized? Ideal Point Estimation using Real-Time Debate Reactions,” with Daniel Argyle, Philip Resnik, and Vladimir Eidelman.
Political scientists have not reached a consensus about whether the apparent and well documented polarization among political elites exists to the same extent among the mass public. The primary challenge in identifying levels of polarization in the mass public is accurate, robust, and unbiased estimation of individual-level ideology. Ideal point models have become a powerful tool in understanding the ideology of many kinds of political actors, including – but not limited to – legislators. We extend the application of ideal point models to members of the mass public by using their real-time reactions to statements by candidates in the 2012 presidential debates. We consider the idea that simply reacting to a political statement is itself a kind of vote amenable to ideal-point analysis. We use the discrete reactions provided by thousands of debate viewers using a mobile real-time response app (Boydstun, Glazier, et al. 2014) to estimate their ideal points. The resulting ideal points are consistent with observed vote totals in the election and demographic attributes of the respondents.Unlike the bimodal ideal point distribution commonly seen in legislative bodies, we find that the debate reactions have a unimodal ideal point distribution. Compared to political elites, we find no evidence of ideological polarization in the public.
“Inequality and Economic Redistribution on College Campuses,” with Tali Mendelberg
“Political Polarization, Social Media Echo Chambers, and American Public Opinion: A Field-Experiment on Twitter,” with Chris Bail, Mary Beth Fallin Hunzaker, Taylor Brown, Marcus Mann, Friedolin Merhout, Haohan Chen, John Bumpus, and Jaemin Lee.
“How Do We Know what They Know? Feasibility, Reliability, and Validity of Undergraduate Program Evaluation through Portfolio Assessment,” with Margarita Safronova and Cecilia Farfan-Mendez. Presented at the 2015 American Political Science Association Teaching and Learning Conference.