
Introduction to Text Analytics
A Guide for Digital Humanities & Social Sciences
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
This easy-to-follow book will revolutionise how you approach text mining and data analysis as well as equipping you with the tools, and confidence, to navigate complex qualitative data.
It can be challenging to effectively combine theoretical concepts with practical, real-world applications but this accessible guide provides you with a clear step-by-step approach.
Written specifically for students and early career researchers this pragmatic manual will:
• Contextualise your learning with real-world data and engaging case studies.
• Encourage the application of your new skills with reflective questions.
• Enhance your ability to be critical, and reflective, when dealing with imperfect data.
Supported by practical online resources, this book is the perfect companion for those looking to gain confidence and independence whilst using transferable data skills.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Contents
- About this Book
- About the Author
- Online Resources
- Part I Basic Concepts and Tools for Text Analytics
- 1 Computational and Traditional Text Analysis
- 2 Basic Tools for Text Analytics
- 3 Dataset Creation and Considerations
- Part II Language and Computers
- 4 Language as Data
- 5 Regular Expressions
- Part III Programming for Text Analytics
- 6 Introduction to Python Programming
- 7 Preprocessing Textual Data
- 8 Data Manipulation and Exploration
- 9 Data Visualization
- Part IV Social Media Analytics
- 10 Text Mining
- 11 Social Media Analysis
- 12 The Basics of Machine Learning
- Part V Publishing
- 13 LaTeX Basics
- Acronyms
- Glossary
- References
- Index