Humanities data in R: exploring networks, geospatial data, images, and text (second edition). Taylor Arnold and Lauren Tilton

Extract

Exploratory data analysis (EDA), introduced by Tukey (1970), enables researchers to go beyond the raw data and uncovers underlying patterns and insights. As a result, it has become an essential tool in digital humanities (DH) studies, where the goal is to observe, describe, and interpret data within the context of humanities research (Evans and Rees 2012; Bod 2022; Yan, Li, and Liu 2024). Given the significance of EDA in DH studies, the book under review, authored by Taylor Arnold and Lauren Tilton, serves as a valuable resource for humanities students and scholars seeking to explore humanities data using R, a widely-used programming language. In this book, the authors use straightforward language along with well-structured code to demonstrate how to handle various types of humanities data in R and visualize them effectively. The newly-released second edition marks a significant improvement over the first edition, primarily due to the incorporation of the widely-utilized tidyverse packages (Wickham et al. 2019), including ggplot2, dplyr, and others, which enable readers to perform data processing and visualization with greater efficiency and ease.