Last Updated on May 16, 2022 by Anna Pacholczyk

MediaFutures Work Package 3 Leader Bjørnar Tessem alongside Lars Nyre, Michel d.S. Mesquita & Paul Mulholland contributed with a chapter in the book “Futures of JournalismTechnology-stimulated Evolution in the Audience-News Media Relationship».

The chapter’s title: Deep Learning to Encourage Citizen Involvement in Local Journalism


We discuss the potential of a mobile app for news tips to local newspapers to be augmented with artificial intelligence. It can be designed to encourage deliberative, consensus-oriented contributions from citizens. We presume that such an app will generate news stories from multi-modal data in the form of photos, videos, text elements, location information, and the identity of the contributor. Three scenarios are presented to show how image recognition, natural language processing, narrative construction, and other AI technologies can be applied. The scenarios address three interrelated challenges for local journalism. First, text and photos in tips are often of low quality for journalism purposes. Second, peer-to-peer dialogue about local news takes place in social media instead of in the newspaper. Third, readers lack news literacy and are prone to confrontational debates and trolling. We show how advances in deep learning technology makes it possible to propose solutions to these problems.