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Introduction to Text Analysis : A Coursebook

Introduction to Text Analysis : A Coursebook

Edition:

Author(s) :Brandon Walsh; Sarah Horowitz

Year :2017

ISBN :

Pages :161\161

Language :English

Extension :PDF

Size :15 MB (15227976 byte

Summary :

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. Table of contents : Preface Acknowledgements Introduction For Instructors For Students Schedule Issues in Digital Text Analysis Why Read with a Computer? Google NGram Viewer Exercises Close Reading Close Reading and Sources Prism Part One Exercises Crowdsourcing Crowdsourcing Prism Part Two Exercises Digital Archives Text Encoding Initiative NINES and Digital Archives Exercises Data Cleaning Problems with Data Zotero Exercises Cyborg Readers How Computers Read Texts Voyant Part One Exercises Reading at Scale Distant Reading Voyant Part Two Exercises Topic Modeling Bags of Words Topic Modeling Case Study Exercises Classifiers Supervised Classifiers Classifying Texts Exercises Sentiment Analysis Sentiment Analysis Sentiment Analysis in Action Exercises Conclusion Where to Go Next Further Resources Adapting This Book
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About book:

Book category:2017

Book views:915

Eidt day:2017-09-15




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