Distant Reading in Theory and Practice:
Computational Approaches to Text Analysis
This survey course introduces distant reading concepts, methods, and techniques such as data mining, sentiment, textual analysis, word embedding, and topic modelling. It is not a math course; however, it will introduce students to concepts in data science, data collection, data cleaning, statistics, and machine learning as they are relevant to the Digital Humanities. By employing examples and case studies, as well as incorporating participants’ own data, this course will offer an opportunity for participants to gain hands-on experience collecting data, curating data, and employing distant reading techniques.
Anyone with an interest in digital humanities and language. While this course will employ Python, no prior programming experience is necessary.