This pioneering book teaches readers to use R within four core
analytical areas applicable to the Humanities: networks, text,
geospatial data, and images. This book is also designed to be a bridge:
between quantitative and qualitative methods, individual and
collaborative work, and the humanities and social sciences. Humanities
Data with R does not presuppose background programming experience.
Early chapters take readers from R set-up to exploratory data analysis
(continuous and categorical data, multivariate analysis, and advanced
graphics with emphasis on aesthetics and facility). Following this,
networks, geospatial data, image data, natural language processing and
text analysis each have a dedicated chapter. Each chapter is grounded in
examples to move readers beyond the intimidation of adding new tools to
their research. Everything is hands-on: networks are explained using
U.S. Supreme Court opinions, and low-level NLP methods are applied to
short stories by Sir Arthur Conan Doyle. After working through these
examples with the provided data, code and book website, readers are
prepared to apply new methods to their own work. The open source R
programming language, with its myriad packages and popularity within the
sciences and social sciences, is particularly well-suited to working
with humanities data. R packages are also highlighted in an appendix.
This book uses an expanded conception of the forms data may take and the
information it represents. The methodology will have wide application in
classrooms and self-study for the humanities, but also for use in
linguistics, anthropology, and political science. Outside the classroom,
this intersection of humanities and computing is particularly relevant
for research and new modes of dissemination across archives, museums and
libraries.
