“There’s a movement where people share information, thoughts and creativity which the journalism world is not automatically a part of,” explains Michael Bröcker, editor of Rheinische Post about its Trend Recognition tool.

Online information continues to grow, spreading rapidly. This makes it increasingly challenging for conventional news organisations to process and trace stories quickly and accurately. More and more journalists are gathering information from online ‘filter bubbles’, and it’s less easy to break stories the right way. And when quality news fails to drive the agenda, it creates a space for false news to do so instead.

For Michael, this created a clear need for a new approach: “We needed to improve our technology to see what is on the minds of people. If we didn’t, journalism may not be here in ten, twenty years.”

Bröcker tasked his team with building a set of social listening tools to provide journalists with a way to identify important stories before they went viral. In his words, “We need to be relevant and we need to stay relevant, and this only works if we understand what’s out there in the social web.” They developed The Listening Center, and with it the Trend Recognition Module.

“The Listening Center is a suite of tools keeping track of 400 million data sources,” says Daniel Fiene, editor of The Listening Center. “When something is shared, within one minute it is in our system.”

The software identifies topics relevant to each journalist and measures their social impact to identify global or local trends. It allows them to gauge the potential for an important story to build within the next few hours or days.

Daniel explains that the Listening Center spans across digital platforms: “It’s not just social media. It’s news sites, discussion boards and other platforms – every journalist has access to the reportings. It creates more room for quality journalism because we save so much time.”

He also emphasises that support from the DNI Fund allowed the team to take the project to the next level:  

“With the DNI Fund, we were able to bring the trend recognition module where we could actually predict viral stories. We were quicker on stories and we were better informed about what’s going on in our region.”