ginic/oxfam-text-analysis

Dagstuhl AI for Social Good Hackathon Collaboration with Oxfam Novib

Oxfam and UMass Amherst Collaboration at AI for Social Good, Dagstuhl

This repository is one outcome of the hackathon at the Dagstuhl AI for Social Good conference in Feburary 2024.

Getting started

Installing Dependencies and Packages

This repository was created from the UMass Amherst Center for Data Science python project template. If you have questions about the package file structure or python dependency, installation there are more details at this link. Use these steps for setting up a development environment to install and work with this code:

1. Set up a Python 3 virtual environment using Conda or Virtualenv. Read Python Virtual Environments: A Primer for details on how to get started with virtual environments and why you need them.

2. Activate your virtual environment.

3. Install the package.

   • If you want to just use the scripts and package features, install the project by running pip install . from the root directory.
   • If you will be changing the code and running tests, you can install it by running pip install -e .. The -e/--editable flag means local changes to the project code will always be available with the package is imported. You wouldn't use this in production, but it's useful for development.

Running Jupyter Notebooks for Exploration

The initial exploration from the hackathon is in notebooks/exploration.ipynb After you have installed the dependencies, you can run jupyter notebook or jupyter lab, then open exploration.ipynb. See the jupyter documentation for more details.

Note that the jupyter notebook with images and data outputs is too big to be committed to Github, so after you run the notebook, you can export it to pdf using nbconvert. Then clear the notebook outputs, save and commit.