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Digital Humanities Tools and Resources

Use this guide to learn about the field of Digital Humanities, software tools for humanist research, and resources to get started on new projects.

Text Analysis & Data Mining


Computational text analysis tools allow scholars to read bodies of text in new ways by using machine learning to pick up on word frequency patterns in texts. This process, often called “distant reading” or “topic modeling,” can complement traditional close reading by providing insights into patterns such as word usage, psychological tendencies, and language commonly associated with historical events, etc. that a human might not be able to easily notice without the assistance of computational tools. To explore the capabilities of text analysis programs, please refer to the list of commonly used tools below. 



​Argamon, S., & Olsen, M. (2009). Words, patterns, and documents: Experiments 
in machine learning and text analysis. Digital Humanities Quarterly, 3(1). Retrieved from
Brett, M. (2012). Topic modeling: A basic introduction. Journal of the
Elliot, T., & Gillies, S. (2009). Digital geography and classics. Digital Humanities
Gregory, I., Donaldson, C., Murrieta-Flores, P., & Rayson, P. (2015). Geoparsing,
GIS, and textual analysis: Current developments in spatial humanities research. International Journal Of Humanities & Arts Computing: A Journal Of Digital Humanities, 9(1), 1-14.

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