Storylines for structuring massive streams of news

Stories are the most natural ways for people to deal with information about the changing world. They provide an efficient schematic structure to order and relate events according to some explanation. We describe (1) a formal model for representing storylines to handle streams of news and (2) a first implementation of a system that automatically extracts the ingredients of a storyline from news articles according to the model. Our model mimics the basic notions from narratology by adding bridging relations to timelines of events in relation to a climax point. We provide a method for defining the climax score of each event and the bridging relations between them. We generate a JSON structure for any set of news articles to represent the different stories they contain and visualize these stories on a timeline with climax and bridging relations. This visualization helps inspecting the validity of the generated structures.

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