https://at-ceu.studyguide.timeedit.net/modules/DOPP5688?type=COREThis course introduces students to computational text analysis and Natural Language Processing (NLP) techniques for public policy research. It covers text preprocessing, dictionary-based methods, topic modeling, sentiment analysis, and advanced machine learning applications. Students will gain hands-on experience analyzing policy documents and social media data. Through practical case studies, students will learn to extract meaningful insights from unstructured text and collect text from various sources. The primary language of instruction will be R. By the end of the course, students will be equipped with the skills to apply text-as-data methods to inform public policy decisions.Part of the Quantitative Policy Analysis specialization for MAPP and MPAPart of both the Democracy and the Policy track courses for MAIPA