Physics

Ranking (information retrieval)

Prestige

Event (particle physics)

Mathematics

Domain (mathematical analysis)

Literature

Mathematical analysis

Philosophy

Artificial intelligence

Psychology

Narrative

Natural language processing

Data science

Popularity

Computer science

Linguistics

Literal and figurative language

Quantum mechanics

Social psychology

In this work we present a new dataset of literary events—events that are depicted as taking place within the imagined space of a novel. While previous work has focused on event detection in the domain of contemporary news, literature poses a number of complications for existing systems, including complex narration, the depiction of a broad array of mental states, and a strong emphasis on figurative language. We outline the annotation decisions of this new dataset and compare several models for predicting events; the best performing model, a bidirectional LSTM with BERT token representations, achieves an F1 score of 73.9. We then apply this model to a corpus of novels split across two dimensions—prestige and popularity—and demonstrate that there are statistically significant differences in the distribution of events for prestige.

Literary Event Detection