Days and Times: MoWe 1:30-2:50pm
Room: WEH 5201 (CMU Campus)
Instructor: Suguru Ishizaki
This course is a pre-approved elective for Fall Term 2019.

This introductory course provides humanities students with the foundational knowledge and skills to develop computer-aided research tools for text analysis. Through a series of hands-on coding exercises, students will explore computation as a means to engage in new questions and expand their thinking about textual artifacts. This course is designed for students with no (or very little) coding experience. During the early part of the semester, students will learn basic programming using Python through examples and problem sets that are relevant to text analysis. Then, students will be introduced to a limited set of commonly used Python packages for text analysis, such as natural language processing, statistical analysis, visualization, web scraping, and social media text mining. Students are expected to complete a small final project that examines how evidence-based data-driven insights derived from text analysis would support humanistic research in their area of interest, including (but not limited to) genre studies, rhetorical criticism, authorship attribution, discourse analysis, cultural analysis, social network analysis, spatial/temporal text analysis, and writing assessment. Doctoral students in the Department of English must register for 12 units, and are expected to write a publishable quality paper. 

**Please contact DSAM Graduate Advisor, Alison Langmead (alangmead@pitt.edu), for information about enrolling in this course.**