Full Description
Grounded in examples from across the social sciences, this book walks you through the process of doing quantitative text analysis step by step. Clear and accessible, it empowers you to progress from beginner level to understanding and using computational social science concepts with ease. Covering key steps in the research process like ethics, data collection, and model choice, it helps you develop important research skills - and equips you with the programming tools you need to handle text data without error.
The textbook offers R software guidance at an easy-to-follow pace, the book presents the coding skills you need to collect and prepare data, providing a strong foundation as you move into data analysis. It will:
· Help you develop key data skills like cleaning, managing, classifying and visualizing data
· Encourage your ability to be critical and reflective when dealing with data
· Offer clear guidance on using messy, real-world data and big data from sources like Wikipedia
Supported by practical online resources including extensive coding examples and software guidance, this book will give you confidence in applying your programming skills and enable you to take control of handling textual data in your own research.
Contents
Chapter 1: Calculating with Letters
Chapter 2: Using R for Text Analysis
Chapter 3: Text as Data: Obtaining, Preparing, and Cleaning
Chapter 4: Extracting and Visualising Information from Text
Chapter 5: Supervised Machine Learning for Text Data
Chapter 6: Unsupervised Machine Learning for Text Data
Chapter 7: Evaluation and Validation of Quantitative Text Analysis
Chapter 8: Using Python within R for QTA
Chapter 9: Communicating Text Analysis
