Research

How can we build common ground across party lines?

One major challenge confronting contemporary societies, including the U.S. and many countries around the world, is the threat of misinformation and increasing partisan disagreements on what constitutes fact. Partisan polarization on factual beliefs can obstruct cooperation and reconciliation, even to the point of jeopardizing the legitimacy of political institutions and processes. I study how we can mitigate the partisan divide and build common ground by increasing the credibility of evidence-based information and by invoking shared emotions and experiences.

Theme 1: Building Bipartisan Trust in Evidence-based Sources

Political fact-checking, a genre of reporting dedicated to assessing the accuracy of political claims, was initiated in the early 2000s by FactCheck.org, PolitiFact, and the Washington Post’s Fact Checker. The non-partisan, evidence-based approach of political fact-checking is important in polarizing environments, because it can potentially build common factual ground across party lines. However, despite the growth of fact-checking, it remains uncertain whether fact-checking sources have succeeded at convincing both partisan groups. In my dissertation, by analyzing how fact-checking norms and practices affect partisans’ source assessments, I examine obstacles to and prospects for bipartisan trust in political fact-checking. 

Dissertation: Building Bipartisan Trust in Political Fact-checking

  • ​“Why Does Fact-checking Inspire Partisan Distrust? The Effects of Asymmetric Coverage on Source Credibility” (Job Market Paper)

  • "Why Favorable Views but Limited Use of Fact-checking? Familiarity with and Trust in Fact-checking Sources and Conventional Media.”

  • “Achieving Democratic Accountability via Fact-checking: The Effects of Topic Coverage Scope on Source Credibility.”

Theme 2: The Role of Shared Emotions and Experiences

Many studies have identified psychological mechanisms that reinforce partisan divisions, but less is known about what can help mitigate partisan divisions. Apart from my dissertation, I have conducted experimental studies that examine shared experiences and emotions as a potential bridge that can help partisans converge on factual perceptions.

  • “Impede or Imperil? Distinguishing the Roots of Public Anger and Fear” with Ted Brader and Erin Cikanek.

  • “Can Disaster Experience Mitigate the Partisan Divide on Climate Change? Evidence from Texas” with Christopher Fariss, Ted Hsuan Yun Chen, and Xu Xu.

  • "Can Corruption Trigger Democratic Accountability? Corruption Scandals, Personal Concerns, and Blame Attribution in South Korea." with Deanna Kolberg.

Theme 3: Improving Measurement and Inferences in Political Science

My secondary research interest lies in enhancing measurements and inferences of political science research. Using latent variable models, I develop and refine measurements of psychological traits and attitudes that are not directly observable. I also examine the historical trajectory of statistical significance claims in social science in light of increasing computing power, in search of more effective inferences.

  • “The Reasoning through Evidence versus Authority (EvA) Scale: Scale Development and Validation” with Stephanie Preston and Priti Shah. (Under Review)

  • “Ordered Bayesian Aldrich-McKelvey Scaling: Improving Bias Correction on the Liberal-Conservative Scale” with Kevin McAlister and Erin Cikanek.​

    • Received the Samuel Eldersveld Outstanding Paper Award, Department of Political Science, University of Michigan. 2019.​

  • “What Can We Learn from Social Science’s Steroid Era? A Proposal to Reinterpret Fifty Years of Statistical Significance Claims” with Arthur Lupia, Rocío Titiunik, and Nicolás Idrobo.​