Introduction to Computational Social Science Syllabus
Description
Course Information
Computational social science uses data, code, and social theory to study political and social life at scales that were difficult to observe only a few years ago. This syllabus seeks to introduce students to that field through substantive questions about politics, public policy, international relations, social media, institutions, and economic governance. Students will learn how to collect, clean, visualize, model, and interpret social data using the R programming language and reproducible Quarto documents.
The course gives special attention to text as data. Political life is made of speeches, manifestos, policy documents, news articles, social media posts, parliamentary debates, central bank communications, NGO reports, and other forms of language. We will learn how to transform texts into analyzable data without forgetting that texts are produced by people, institutions, and unequal social contexts. Students will work with methods including corpus construction, tokenization, descriptive text statistics, dictionaries, supervised classification, topic models, scaling, and introductory large language model workflows.