Teaching

This course introduces students to the quantitative analysis of text as data. With the increasing availability of large-scale textual data – from government documents and political speeches to social media and online news – the potential to extract meaningful insights from text has expanded greatly. In this course, students will learn to transform text into data and apply it to social science questions and theories. Some of the key topics include dictionary construction, sentiment analysis, scaling text on ideological and policy dimensions, and using machine learning for text classification. Although we will touch on concepts such as large language models, the focus is on applied methods rather than an in-depth coverage of natural language processing techniques. The course includes hands-on exercises using real-world data to reinforce lecture content. By the end, students will have a toolkit for text analysis useful in roles as policy experts and computational social scientists. Students should have completed at least an introductory statistics course and have a basic understanding of probability, distributions, hypothesis testing, and linear models. Students are also expected to have experience working with R, the programming language and software environment of this course.

Social media has become a significant force in shaping politics, economics, development, culture, and intergroup relations. This course examines its global relationship with political behavior, analyzing how it influences the attitudes, beliefs, and actions of citizens and policymakers, and how political behavior in turn shapes online platforms. We will examine how social media shapes social cohesion and polarization, political engagement, news consumption, among other outcomes, alongside the psychological processes that drive these dynamics. The course also introduces students to cutting-edge research methods for assessing social media's effects, as well as interventions designed to harness its potential for positive governance outcomes. In addition to theoretical grounding, we will learn about the data and methods for studying social media, including causal reasoning with observational data and evaluating validity of inferences from large-scale datasets. By the end, students will be equipped to analyze social media's role in politics, assess policy implications, and communicate their insights effectively.