I am currently Postdoctoral Fellow in Data Science at the Social Media and Political Participation (SMaPP) Lab, NYU.

My research sits at the intersection of political communication, public opinion, and political behavior. I use a combination of experimental methods, large datasets, machine learning, and innovative measurement to study how people choose, process, spread, and respond to information about politics. This fall, I will join the Princeton University faculty as an assistant professor of politics and public affairs.

Current or recent projects investigate online selective exposure, how to accurately measure media exposure on the internet, the dynamics of interest group mobilization over Twitter, and the persuasive effect of new information on individuals’ attitudes and beliefs. See the Research page for more on these and other projects.

Please find me on Google Scholar, ORCID, Dataverse, Github, and, of course, Twitter.

New! “Media Choice and Moderation: Evidence from Online Tracking Data”

Does the internet enable selective exposure to congenial content? This is the first study of online media consumption to combine large-N passive tracking data with individual-level political variables on a representative cross-section of Americans. I find that most people across the political spectrum have centrist media diets composed largely of mainstream portals: The average slant of Democrats’ and Republicans’ media consumption differs by less than 8% of the available ideological spectrum of online sources. An exception to this pattern is a small group of partisans who drive a disproportionate amount of traffic to relatively extreme websites, particularly on the right. I extend this powerful empirical approach by testing how exogenous changes in the offline political environment affect the types of sources people use to learn about the news. I do this in two ways: first, by deploying an online field experiment about a novel political issue, and second, by exploiting revelations about a major scandal that emerged during data collection. In doing so, I explore the mechanisms of information search underlying the unique observational portrait this approach enables. Theoretically, I outline a distinction between “active” and “passive” search and show that engaging in more purposeful political media consumption can result in either polarization or moderation, depending on the context. Overall, the findings support a view that if online “echo chambers” exist, they are a reality for only very few people who drive the traffic and priorities of the most partisan outlets.