Mapping Texts is the first introduction to computational text analysis that simultaneously blends conceptual treatments with practical, hands-on examples that walk the reader through how to conduct text analysis projects with real data. The book shows how to conduct text analysis in the R statistical computing environment--a popular programming language in data science. This book could not be more welcome. Authored by two of the leading sociological researchers in the field of text analysis, it offers a comprehensive guide to state-of-the-art text analysis methods. But beyond just an introduction to methods, it provides a thoughtful and theoretically informed engagement about how we should think about, and interpret, the wealth of textual data that is now available. This is essential reading for anyone with an interest in computational social science.