Journalism + data science projects

Practical, real-world examples of machine learning and statistics used in journalism.

The National Highway Transportation Safety Administration receives thousands and thousands of vehicle complaints each year. Can we train a computer to filter out leads on Takata airbag malfunctions?

Standard sentiment analysis scores a document on a positive-vs-negative scale. Using the Emotional Lexicon, though, you can add unique emotional measurements like anger, joy, surprise, or fear.

Combine geographically granular life expectancy data with the American Community Survey to see how poverty, education, income, and demographics can affect a community.

From a list of points along a flight's path, how can you say "this looks like a surveillance plane?" And once you've found them, what do you do with the results?

When selecting a jury, both the defense and the prosecution are allowed to strike potential jurors from the pool. While the potential jurors provide answers to a questionnaire, what kind of role might race play in their selection or rejection?

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