I apply computational approaches to social questions. My data come from lab studies, field studies, and web-based observational research.
Intergroup relations in the digital world
The increase in the use of digital devices has changed the way we connect with each other and the way we consume information. Additionally, these machines have effectively become constant data-collection devices that reflect our social behavior. This line of research leverages these societal changes to discover behavioral consequences of widely communicated stressful events. Using computational methods, I’m able to study phenomena that have been difficult or impossible to study with more traditional social psychological methodology.
Reducing inequality through interventions
Historically, stigmatized groups have been disadvantaged in some important life domains. One branch of my work explores methods to reduce this inequality. Specifically, I’ve been exploring boundary conditions and mechanisms of a written intervention known as a values affirmation. The goal of this work is to use unify disparate datasets to better understand how the intervention works across diverse settings, and to use computational methods to find linguistic features that can highlight why and for whom the intervention works.
Communication of science
The way in which we communicate our own work is of fundamental importance for our work, as well as for the perception of our work by outside parties. In a third line of work, I’m using the papers we produce as researchers as the basic unit of analysis. In this work, I’m exploring how we communicate our science, with an eye toward documenting how we communicate statistical results. What properties of our data do we highlight, and what parts do we neglect? When do we communicate confidence versus uncertainty? These questions take on increased importance given the current debates over the fundamentals of our research methodology.