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The Usable Privacy Policy Project develops techniques to semi-automatically analyze privacy policies with crowdsourcing, natural language processing, and machine learning. You can explore some of the project’s privacy policy annotations which identify different data collection and use practices.

Data presented here are made available for research and teaching. Our results showcase both the power and limitations of human and machine annotation.

Human-Annotated Privacy Policies

Annotations by law students on a set of 115 privacy policies collected in 2015. These annotations were used to train our classifiers.

Browse the Human-Annotated Policies

Machine-Annotated Privacy Policies

Annotations generated by our machine learning classifiers for a set of over 7,000 privacy policies collected in 2017.

Browse the Machine-Annotated Policies

This project is funded by the National Science Foundation under its Secure and Trustworthy Computing initiative (CNS-1330596).