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. 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

My research seeks to clarify conditions under which Democrats and Republicans can converge on trusted news sources. By doing so, I aim to address the deep-seated and troubling social problem of a partisan divide over basic facts.

Dissertation: Building Bipartisan Trust in Political Fact-Checking

My dissertation focuses on political fact-checking, a genre of reporting dedicated to assessing the accuracy of political claims, which was initiated in the 2000s by FactCheck.org, PolitiFact, and the Washington Post’s Fact Checker. The nonpartisan, evidence-based approach of fact-checking can potentially build common factual ground across party lines. However, it remains uncertain whether fact-checking has succeeded at convincing both partisan groups. I examine obstacles to and prospects for bipartisan trust in political fact-checking by analyzing how fact-checking norms and practices affect partisans’ source assessments. 

Theme 2: The Role of Shared Experiences and Emotions

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 and achieve democratic accountability.

Theme 3: Improving Measurement and Inferences

My secondary research interest lies in enhancing measurements and inferences in social science research. Using latent variable models, I develop and refine measurements of psychological tendencies 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.