Newsworthy
Automated story finding for journalists
A team of leading data journalists and a PhD student in statistics automated the process of finding news in data. Newsworthy re-uses Open Data to help local reporters find stories in data. Monitoring statistical databases with bayesian statistical models allows to process haystacks of data to find the interesting needles.
Newsworthy notifies subscribers when it finds local trends and anomalies in data: a theft peak, a new trend in housing prices or a temperature record. These so called newsleads will be sent to subscribers presented in a short text, a chart and an excel sheet with underlying data. The goal is to give journalists all the context needed to either publish a simple news story or dwell into further research on a topic. The process takes three steps:
- Pick regions and topics to monitor.
- Newsworthy analyses large amounts of data to find newsleads.
- Receive an e-mail with a story in one of the selected regions.
Subscribe to Newsworthy or read more about Data-Driven Journalism.