How to (Machine) Read a Novel: Modeling Events and Information in Literary Fiction

Special Event | January 14 | 5:30-6:30 p.m. |  South Hall

 Matthew Sims

 Information, School of

Novels pose unique challenges that tend to be overlooked by current natural language processing systems. The number of different characters and sheer length of the text limit the effectiveness of state of the art coreference approaches. The extensive use of figurative language complicates how we define and identify events. The patterns and structures through which information is propagated between characters is highly distinct from how information is diffused across social media, the primary focus for this kind of research. In this webinar, Iâll discuss some of the difficulties that arise when building models to analyze fiction as well as how these challenges in turn make the literary domain potentially relevant to broader questions in the field of NLP. In particular, Iâll present two recent research projects, one on identifying events in fiction and the other on literary information propagation.