Humanities Data in R

Exploring Networks, Geospatial Data, Images, and Text

  • Taylor Arnold
  • Lauren Tilton

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Basics

    1. Front Matter
      Pages 1-1
    2. Taylor Arnold, Lauren Tilton
      Pages 3-6
    3. Taylor Arnold, Lauren Tilton
      Pages 7-24
    4. Taylor Arnold, Lauren Tilton
      Pages 25-46
    5. Taylor Arnold, Lauren Tilton
      Pages 47-61
    6. Taylor Arnold, Lauren Tilton
      Pages 63-78
  3. Humanities Data Types

    1. Front Matter
      Pages 79-79
    2. Taylor Arnold, Lauren Tilton
      Pages 81-94
    3. Taylor Arnold, Lauren Tilton
      Pages 95-111
    4. Taylor Arnold, Lauren Tilton
      Pages 113-129
    5. Taylor Arnold, Lauren Tilton
      Pages 131-155
    6. Taylor Arnold, Lauren Tilton
      Pages 157-176
  4. Appendix

    1. Front Matter
      Pages 177-177
    2. Taylor Arnold, Lauren Tilton
      Pages 179-182
    3. Taylor Arnold, Lauren Tilton
      Pages 183-192
    4. Taylor Arnold, Lauren Tilton
      Pages 193-211

About this book

Introduction

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 scientists. Exploring Humanities Data Types 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). 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. The book’s data, code, appendix with 100 basic programming exercises and solutions, and dedicated website are valuable resources for readers. 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.

Keywords

Exploratory Data Analysis in the Humanities Geospatial Data R Humanities Data with R Image Data R Natural Language Processing Network Analysis R Textbook Humanities R packages for Humanities Text Analysis with R Visualization

Authors and affiliations

  • Taylor Arnold
    • 1
  • Lauren Tilton
    • 2
  1. 1.Yale UniversityNew HavenUSA
  2. 2.Yale UniversityNew HavenUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-20702-5
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-20701-8
  • Online ISBN 978-3-319-20702-5
  • Series Print ISSN 2199-0956
  • Series Online ISSN 2199-0964
  • About this book