Local newspapers with limited markets and even more limited resources are having a tough time of it in the digital age. But a new project offers rays of hope.
A project called RADAR (Reporters and Data and Robots) begun in the UK is managing to produce some 8,000 local stories per month with a staff of only five data reporters and two editors. These stories are distributed through a wire service. The stories produced by the data reporters are then run through a template that an AI process transforms into multiple localized stories.
Nicholas Diakopoulos explains in greater detail in this report from the Columbia Journalism Review:
A key to the success of the RADAR process is that human journalists determine what angles, trends, or outliers are newsworthy in the data and structure the template for the various versions of the article. The automation then helps to locally adapt the writing, and if needed a local journalist can add to it to improve the local relevance.
The government datasets used by RADAR help to highlight municipal problems in hospitals, with street crime, and in public services like firefighting or education. “Their understanding of the regional news agenda seems to be pretty much in tune with the kind of content we’re interested in,”(Tim) Robinson explains. To get a feel for the range of content, you can see the feed of weekly advisories RADAR publishes to Twitter. It’s not just fluff—the content is filling a real gap in local coverage for under-resourced publishers.
Another benefit to using open government datasets is that they’re freely available. Government has already invested the money and effort to collect the data, and RADAR leverages the data to add value for newsrooms… While RADAR has filed a few public records requests to get data, that labor-intensive process often involves a lot of data tidying once it’s received and may not spark joy. Rogers says RADAR isn’t looking to get into gathering their own data just yet. “There’s so much available for us in public data that we’re not even touching,” he explained.
