MDST 166. Introduction to Computational Literary Analysis (1). Is it possible to count, or quantify, the qualitative features of writing, whether a poem, a newspaper article, or a novel? In this course students are introduced to the field of computational literary analysis as a subfield of the digital humanities. They learn how humanists use quantifiable data and metadata; and, they learn to formulate research problems and questions that lead to a computational approach to literary/textual analysis. Topics covered: the Google Ngram Viewer and Ngram Dataset, basic Python programming; and the functionality of the NLTK (Natural Language Toolkit) and SpaCy Python libraries. Prerequisites: none.