Labelit is a simple and straightforward tool for fast anonymization or pseudonymization and labeling of text data. This is particularly relevant if you're planning to work with text corpora (e.g. twitter posts) that contain a lot of personal references. Labelit allows you to remove personal information while maintaining the informational and semantical content. On top of that, with Labelit you can label text corpora with self-selected classes - a necessary preprocessing step for all kinds of quantitive analyses.
Just create a project, import your data, create categories for named entities and start replacing sensitive information with your predefined words.
Warning: The software is still in early development and currently only works in a local enviroment. Do not use it on a remote server, there is no file upload yet. Labelit does not work in Safari and IE (no support planned).
Requirements
Make sure that you installed Node.js and MongoDB is running:
git clone https://github.com/Mirobit/Labelit.git
cd Labelit
npm install --production
Now open the .env.example
file and follow the instructions.
To start the app, simply run:
npm start
Go to your browser and enter http://localhost:8000/
.
Use admin
as username and the password from the .env
file to sign in.
See GUIDE.md and check the examples folder, to see how the input data needs to be structured. See MongoDB.md to find out how to change the MongoDB database location.