Graduate Research Symposium Awards

The Graduate Student Advisory Council (GSAC) hosted their annual (Virtual) Graduate Research Symposium on Saturday, June 6, 2020. We are honored to report that our Department's Applied Statistics MS student, Tim Mitchell, was awarded this year's "Outstanding Paper/Presentation in the Science" Award. 

Title: Quantitative Methods of Evaluating Song Lyrics

Abstract: Advances in text mining and natural language processing have made it viable to study text using methods normally reserved for numerical data. Here I present an analysis of song lyrics based on a data set of 200,000+ songs scraped from the web. I find that several summary statistics follow a smooth unimodal distribution, including total words, unique words, and percentage of words that are unique. These distributions differ as a function of genre, with large effect sizes observed. One of the biggest challenges in natural language processing is the development of tools to measure and score literary devices. I propose a novel framework to measure consonance scores and present an original unsupervised algorithm that can detect consonance in text data. These provide a statistical basis for comparing frequencies of literary devices across songs, genres, and artists.

Click here to learn more about the Graduate Research Symposium Award winners.