RIPPL Talk: Kevin Munger (Penn State [Princeton 2023]) - "Introducing the Visual Conjoint, with an Application to Candidate Evaluation on Social Media"

There has been an explosion of interest in conjoint experiments within political science, enabling scholars to understand the preferences of citizens in a variety of political contexts. We propose a method to modify the standard text-only “box conjoint” to make the treatment higher in external validity with respect to a common target context. Citizens frequently encounter political information encoded as images and in particular in the form of politicians’ social media posts and profiles. We deploy “visual conjoint” experiments where subjects select between two images that encode denotational information in addition to important implicit cues that cannot be unawkwardly translated into the literal form of that standard conjoint. Furthermore, our approach makes the candidate attributes manipulated in the conjoint differentially salient (rather than uniform) to further enhance external validity. We test the utility of this method in an application where subjects evaluate the Twitter profiles of hypothetical candidates. We demonstrate that the visual conjoint allows subjects to take in image-based information and that it can also incorporate the social endorsement information that is central to politics on social media.