Skip to content

hackasaurus/introduction-to-text-analysis

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Preface

(Note: We welcome feedback on this book! If you find an error, want clarification on a particular issue, or find deep problems with particular explanations, drop us a line on our GitHub issues page. We'll be grateful and list you in our acknowledgements!)

This workbook provides a brief introduction to digital text analysis through a series of three-part units. Each unit introduces students to a concept, a tool for or method of digital text analysis, and a series of exercises for practicing the new skills. In some cases, studies of particular projects are presented instead of tools in the third section of each unit.

The materials here are meant to form the basis for a digital text analysis course that does not require extensive training in programming and is written with student readers in mind. Originally developed for use in a course titled "Scandal, Crime, and Spectacle in the Nineteenth Century," this workbook draws from these course materials for its datasets and prompts. The book is intended to be modularized enough that it could be used in conjunction with other courses either in whole or in part, as all of its materials are openly available on GitHub. The tripartite structure of each chapter means that sections can be easily removed and replaced with different tools or content. In particular, we envision our course-specific exercises in the third section of each chapter to be removable. For more guidance on how to remix the work for your own ends, see Adapting This Book.

The book is best viewed online using either Chrome or Firefox. You can also download it to read as a PDF here.

Introduction to Text Analysis: A Coursebook by Brandon Walsh and Sarah Horowitz is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Creative Commons License

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 58.5%
  • CSS 41.5%