Quantitative Text Analysis for Social Sciences
Instructor: Yongren Shi, PhD
Dates: July 7 – July 11, 2025
Course Description
This five-session course introduces social science researchers to quantitative/computational text analysis using R, blending foundational theory with hands-on practice. Participants will learn to transform raw text (e.g., speeches, social media, news articles) into structured insights using standard tools. The course progresses from text preprocessing and exploratory analysis to advanced techniques such as sentiment analysis, supervised machine learning, topic modeling and word embedding. Sessions combine lecture instruction with practical labs. At the end, participants will use text data for social science research. Prior R experience is strongly recommended but not required.
About the Instructor
Yongren Shi is an Assistant Professor in the department of sociology and criminology, University of Iowa. His research examines how culture, membership, and social networks contribute to stratification and polarization within human groups. In his research, he uses large-scale digital trace data and a range of quantitative and computational methods, including network analysis, computational textual analysis, agent-based modeling, machine learning, online experiments, and survey analysis. Professor Shi’s research has appeared in top sociology and science journals, including American Sociological Review, American Journal of Sociology, Nature Human Behaviour, and Social Forces. His work has been covered by dozens of popular media outlets including Wired, The Guardian, BBC News, Huffington Post, and LA Times. He received the Outstanding Article Publication Award and Dissertation-in-Progress Award from the Mathematical Sociology Section of the American Sociological Association.