Building and Mining Knowledge Graphs for Newsroom Systems

Tracking #: 2179-3392

This paper is currently under review
Arne Berven
Ole A. Christensen
Sindre Moldeklev
Andreas Opdahl
Kjetil J. Villanger

Responsible editor: 
Ruben Verborgh

Submission type: 
Full Paper
Journalism is challenged by digitalisation and social media, resulting in lower subscription numbers and reduced advertising income. Information and communication techniques (ICT) offer new opportunities. The paper explores how social, open, and other data sources can be leveraged for journalistic purposes through a combination of knowledge graphs, natural-language processing (NLP), and machine learning (ML). Our focus is on how these and other heterogeneous data sources and techniques can be combined into a flexible architecture that can evolve and grow to support the needs of journalism in the future. The paper presents the state of our architecture and its instantiation as a prototype we have called {\newshunter}. Plans and possibilities for future work are also outlined.
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