Text Analysis in R
Compiled on: 2025-06-15
Chapter 1 About
Welcome to this BookDown website Text Analysis in R designed to help you process and analyze text in R. The book is broken into five chapters:
1. About
- A brief introduction to the resource
2. Basic Frameworks
- Resources for understanding how psychologists think about text data
- Key definitions and concepts
3. Fundamental Operations
- Importing different types of text data
- Accessing nested text data
- Dealing with garbled text and different encodings
- Cleaning text data and counting words
- Loops to iterate through large amounts of text data
4. Topic Models
- Pre-processing data for stopword removal, contraction expansion, and lemmatizing
- Exploring word frequencies and term frequency-inverse document frequency (TF-IDF)
- Dealing with computational bottlenecks
- Extracting principal components and interpreting topic models
5. Dictionary Methods
- Loading key word lists with quanteda.dictionaries
- Extracting proportions of key words for each document in a corpus
- Examining and interpreting dictionary scores