Computational Historical Thinking
With Applications in R
About this book
Computational Historical Thinking is a textbook that teaches you how to identify sources and frame historical questions then answer them through computational methods. These historical methods include exploratory data analysis, mapping, text analysis, and network analysis. These methods are taught using the R programming language, commonly used by digital historians and digital humanists. Chapters on individual methods ground you in particular approaches, and chapters on case studies of historical research walk you through the process of asking and answering computational history questions.
Work in progress. This book is available while it is being written, and is very incomplete. In particular, chapter numbers are likely to change. Feel free to leave feedback as issues on the GitHub repository, or to e-mail me.
Suggested citation format. If you find this book useful, I would appreciate a citation: Lincoln Mullen, Computational Historical Thinking: With Applications in R (2017): http://dh-r.lincolnmullen.com.
The code for this book is available on GitHub. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.