textAnnotatoR is a comprehensive text annotation tool built with Shiny, designed to facilitate qualitative data analysis through an intuitive graphical user interface. It provides researchers, analysts, and qualitative data scientists with a robust environment for coding text documents, managing code hierarchies, creating memos, and analyzing coding patterns. The package supports collaborative research through standardized annotation formats and provides powerful tools for comparing two coding sets, analyzing code co-occurrences, and visualizing coding patterns.
You can install the development version of textAnnotatoR from GitHub using:
# Install textAnnotatoR
- From CRAN:
install.packages('textAnnotatoR')
- From Github:
::install_github("chaoliu-cl/textAnnotatoR") remotes
Here’s a basic example of how to launch the annotation interface and start coding your text:
library(textAnnotatoR)
# Launch the annotation interface
annotate_gui()
This will open the Shiny application in your default web browser. From there, you can:
The package is structured around several main components:
annotate_gui()
: The main function that launches the
interactive interfaceFor more detailed information, please refer to the package vignettes:
# View available vignettes
browseVignettes("textAnnotatoR")
Key vignettes include: - Getting Started with textAnnotatoR - Managing Code Hierarchies - Analyzing Coding Patterns - Comparing Multiple Coders
textAnnotatoR is designed to work seamlessly with the broader R ecosystem for qualitative data analysis:
readtext
data.tree
for efficient hierarchy
managementshiny
and shinydashboard
for the
interactive interfaceDT
for data display and
manipulationThe package fills a gap in the R qualitative analysis ecosystem by providing a user-friendly GUI while maintaining programmatic access to all functionality.
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.
This project is licensed under the GPL-3 License.
If you use textAnnotatoR in your research, please cite it as:
citation("textAnnotatoR")