From 2020-2024 I worked on a number of projects related to online discourse surrounding COVID-19.

The first such project looked at developing novel methods for monitoring COVID-19 misinformation spreading over social networks. As a member of an interdisciplinary team of researchers at Ohio State University and Northwestern University I formulated approaches to identify misinformation hubs using basic network and data science techniques. You can read more about this work here.

Other projects considered potential links between alternative citations of published research and proponents of non-FDA approved COVID-19 treatments and the undermining of trust in public health officials and institutions through digital content.

My PhD research focused on the modeling of contagious processes, in particular the spreading of disease, behavior, and how those two interact. Using the tools of network science, dynamical systems, and statistical analysis I have examined how the spread of behavior can impact the spread of a disease throughout a population.

In my theoretical projects I investigated how cooperative behaviors spread throughout social networks, as well as how the coupling of behavior and infectious disease impacts the overall dynamics of both. A main finding of my work is that behavioral choices can lead to oscillations between high and low disease prevalence.

In my applied work I ran a study examining the effect of a promotional Twitter campaign on flu vaccination among college students. In this project randomly selected participants were exposed to tweets promoting flu shots. I then combined participants' flu vaccination outcome, Twitter data, and demographic variables to assess the significance of the campaign.