Darknets are portions of the Internet that can only be reached utilizing special protocols or pre-shared knowledge. They operate as overlay networks, transferring information at the application layer of the normal Internet stack, immune to traffic investigations at the normal layers where firewalls and intrusion detection systems live. Darknets, like the Onion Router (TOR) have been used successfully for large-scale cybercrime, including money laundering, drug trafficking, and terrorism. While darknets such as TOR and the Invisible Internet Project (I2P) are currently widely used as investigative avenues by law enforcement and the intelligence community, there is very little large-scale analysis of content and trends over time. The Darknet Weather project would close this gap by producing daily metrics on content availability and distribution, as well as content trends and analysis. This project will then use a combination of text processing and machine learning algorithms to develop trending for topics (examples might include: weapons, drugs, Islamic fundamentalism, etc.). There are already the categories and websites in the hidden wiki to use as an initial training dataset. Then, after a “full crawl” take a snapshot of the statistics and compare it over time to see how and in what areas usage is growing.