Text Analysis (DH203) is an exciting elective course that equips students with the skills to analyze digital texts using computational methods. Over 10 weeks, in hybrid format you’ll dive into the world of text analysis, learning both theoretical and practical techniques to interpret and process large volumes of text data. This course is ideal for students interested in understanding how digital tools can be used to uncover patterns, themes, and insights from a wide range of textual sources. Throughout the course, you’ll work hands-on, developing skills in natural language processing, stylometry, and sentiment analysis. No prior programming experience is necessary, this course is designed to guide you from the basics to more complex methods in a structured, accessible way. Key topics include corpus linguistics, text categorization, clustering, and sentiment analysis, all taught through engaging seminars and practical labs. You’ll analyze everything from literature to social media data, gaining skills that are highly transferable to academic research, publishing, marketing, and data-driven fields. This course combines a solid foundation in humanities with cutting-edge computational techniques. By the end, you’ll be able to perform text analysis, making you a valuable asset in the fast-evolving world of digital media.
