I’m an assistant professor at the University of Missouri where I hold a joint appointment in Journalism Studies with the School of Journalism and Data Science and Analytics with the Informatics Institute. I teach courses in mass media, political communication, quantitative research methods, and data science.


My research uses computational social scientific methods to analyze the selection and dissemination of information in digital media environments. Broadly, I’m interested in selective exposure, new media, data journalism, and data science.

My current work focuses on partisan selective exposure in new media environments. In my dissertation, for example, I studied user networks on Twitter during the 2016 general election. While I found clear evidence of network polarization among partisan users, I also discovered that proximity to the highly-contentious 2016 election had, remarkably, no effect on non-partisan users, suggesting that the real gap in today’s political landscape may not be between Republicans and Democrats but, instead, partisans and non-partisans.

My updated CV can be downloaded here. See my Mizzou J-School faculty page or find me on Twitter, Google Scholar, Github, and Research Gate. Also check out the package website for rtweet, my R package—available on the Comprehensive R Archive Network (CRAN)—for collecting and analyzing Twitter data. If you’d like to make a contribution or report an issue with rtweet, see the Github repository.