Event Detection between Literary Studies and NLP : A Survey, a Narratological Reflection, and a Case Study

The presentation of narrative to the reader is a key aspect of fiction, as information gaps created by the ordering of events create narrative tension. Our objective is to develop a computational model that can detect syuzhet, the way the text presents events to the reader. We have created a theoretical model for the annotation of events in fiction in several languages. Automatic event detection has also been applied in several other domains, such as journalism and history. Due to the lack of consensus on the definition of event within and across domains, previous works demonstrate a wide range of approaches and applications of automated event detection. We give an overview of how previous works differ from each other, and how our model relates to it. We also compare our model to a storyline analysis framework developed for news. We show how our model is applicable on news as well.