BANL 4000 - Text Analytics

Prerequisite: BANL 3100. This course introduces the theory and practice of natural language processing and quantitative text analysis for research applications. It provides a structured framework for managing, analyzing, and interpreting textual data, emphasizing methodological rigor and reproducibility. Students examine the full text analysis workflow, including corpus construction, data cleaning and preprocessing, feature extraction, modeling, and interpretation. The course follows a classical three-stage approach: defining texts and units of analysis, transforming text into quantitative representations, and applying statistical and computational methods for analysis. These methods include dictionary-based techniques, supervised classification, scaling models, and topic modeling. By the end of the course, participants will be equipped to apply both traditional and state-of-the-art text analytics methods to scholarly and applied research contexts. 3 credits.