Overview
textAnnotatoR
provides an interactive graphical user interface for qualitative text analysis in R. The package allows researchers, students, and practitioners to annotate text, manage codes, create memos, and visualize coding patterns through an intuitive Shiny interface.
Key Features
- Interactive Text Annotation: Select and code text segments directly within the GUI
- Code Management: Create, organize, and merge codes with a hierarchical structure
- Theme Organization: Group related codes into themes with a tree-based hierarchy
- Memo Creation: Attach notes and observations to annotations
- Advanced Visualization: Analyze code frequencies, co-occurrences, and patterns
- Comparison Tools: Compare coding patterns between different coders or documents
- Project Management: Save, load, and manage annotation projects
- Export Options: Save annotations and coded text in various formats (CSV, JSON, HTML)
- R Integration: Seamlessly combine with other R packages for advanced analysis
Installation
# Install from CRAN
install.packages("textAnnotatoR")
# Or install the development version from GitHub
# install.packages("devtools")
devtools::install_github("chaoliu-cl/textAnnotatoR")
Getting Started
Launch the annotation interface with a simple function call:
This opens the Shiny application in your default web browser. The interface includes a toolbar for project management, a tabbed main area for different functions, and a text display area.
Basic Usage
- Create a New Project: Click “New Project” in the top toolbar
- Import Text: Go to the “File” tab, upload your text document (.txt, .docx, .pdf)
- Annotate Text: Select text segments and apply codes
- Organize Codes: Create a hierarchical structure of themes and codes
- Analyze Patterns: Use the analysis tools to explore your coding
- Export Results: Save your annotations and analysis for further use
Advanced Features
Code Hierarchies
Create and manage hierarchical code structures with themes and subthemes:
- Use “Add Theme” to create organizational categories
- Group related codes under appropriate themes
- Visualize the hierarchy in a tree structure
Co-occurrence Analysis
Explore relationships between different codes:
- Identify patterns of code co-occurrence
- Visualize connections through network graphs
- Examine statistical measures of code relationships
Integration with R Ecosystem
textAnnotatoR
is designed to work seamlessly with other R packages:
- tidytext: For text mining and natural language processing
- quanteda: For advanced text analysis
- igraph/ggraph: For network visualizations of code relationships
- rmarkdown/shiny: For reporting and interactive dashboards
Contributing
Contributions to textAnnotatoR
are welcome! Please feel free to submit issues or pull requests on GitHub.
Contact
- Issues: Please report issues on the GitHub issues page
- Email: chaoliu@cedarville.edu
- X: @X