This is the second visualization from the project, showing the results of several natural language processing analyses of the original texts. It plots the language patterns embedded in 232,567 pages of historical Texas newspapers, as they evolved over time and space. For any date range and location, you can browse the most common words (word counts), named entities (people, places, etc), and highly correlated words (topic models).
See the visualization at language.mappingtexts.org »
- Mapping Texts is a collaboration between scholars, staff and students at Stanford University and the University of North Texas. It is supported by the National Endowment for the Humanities.
- Historical Topics (1)
- Text Mining (1)
- Uncategorized (1)
- Visualizations (2)