Predicting FOIA requests success rates

Government agencies seem to fulfill or reject FOIA request without rhyme or reason. Can a journalist use machine learning to improve their chances?



Filing FOIA requests can be an unforgiving process, with arcane rules and layers of bureaucracy (and paperwork) to fight through. The FOIA Predictor was a chance to improve the process for weary journalists.

Bannered with "Predict Your FOIA Request Success: This model is trained on 9,000+ FOIA requests tracked by MuckRock" and "a test classification accuracy rate of 80%," the FOIA Predictor appealed strongly to a data journalist's desire for data-driven results, and was reported on accordingly.

But what's going on under the hood? Let's peel back the hood on this open-source project to see what's going on inside.

Notebooks, Assignments, and Walkthroughs

An introduction to machine learning through the FOIA Predictor

Learning about features, models, classification problems, and different evaluation metrics through digging through the insides of the FOIA Predictor.

Multi-page walkthrough