https://github.com/walshbr/introduction-to-text-analysis

https://github.com/walshbr/introduction-to-text-analysis

Last synced: 3 months ago
JSON representation

• Host: GitHub
• URL: https://github.com/walshbr/introduction-to-text-analysis
• Owner: walshbr
• Created: 2016-04-13T20:16:35.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2017-05-17T11:49:29.000Z (over 7 years ago)
• Last Synced: 2024-05-19T23:36:52.161Z (6 months ago)
• Language: Python
• Size: 35.8 MB
• Stars: 25
• Watchers: 7
• Forks: 10
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
Note: We have moved platforms since releasing this book. To see the new and improved version of the book running off Jekyll, check it out [here](http://walshbr.com/textanalysiscoursebook/). Materials here may be slightly out of date.

# 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](https://github.com/walshbr/textanalysiscoursebook/issues). We'll be grateful and list you in our [acknowledgements](acknowledgements.md)!)*

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](https://github.com/walshbr/textanalysiscoursebook). 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](/conclusion/adapting.md). 

The book is best viewed online using either Chrome or Firefox. You can also download it to read as a PDF [here](https://www.gitbook.com/book/bmw9t/introduction-to-text-analysis/details).

*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.