A no-prerequisite online survey course introducing students to the concepts and methodologies of working with, and analyzing primary source texts using digital tools.
Students used the Gale Digital Scholar Lab for content set creation, curation and to clean texts, considering the best practices as well as the limitations of using digital tools for text analysis. Analysis work included clustering, named entity recognition, parts of speech tagging, ngrams, sentiment analysis and topic modeling.
Student projects were built using StoryMapJS and include the following components:
- Title Slide
- Archival resources
- Data curation and text cleaning
- Analysis Summary
- Visualization and analysis results
- Learning summary
The topics chosen by students were wide-ranging, and include sea serpents, Hitler in the Press, the Chicago World’s Fair, organic food and agriculture, Iraq in European newspaper editorials (1991-2013), comparisons of author style, Civil Rights events, the Battle of Bull Run as reported in North and South newspapers, and sentiments about Kim Jong-Un. With student permission, projects are displayed below, each one divided by a separator.