%0 Conference Paper %1 sims-etal-2019-literary %A Sims, Matthew %A Park, Jong Ho %A Bamman, David %B Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics %C Florence, Italy %D 2019 %I Association for Computational Linguistics %K events nlp %P 3623--3634 %R 10.18653/v1/P19-1353 %T Literary Event Detection %U https://aclanthology.org/P19-1353 %X 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.

@inproceedings{sims-etal-2019-literary, abstract = {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.}, added-at = {2021-07-12T16:14:25.000+0200}, address = {Florence, Italy}, author = {Sims, Matthew and Park, Jong Ho and Bamman, David}, biburl = {https://www.bibsonomy.org/bibtex/234e5782e859e62e7d2cc0cc980afcd79/albinzehe}, booktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics}, doi = {10.18653/v1/P19-1353}, interhash = {6a1518da1a26d0e74eb0ca47d5965cb6}, intrahash = {34e5782e859e62e7d2cc0cc980afcd79}, keywords = {events nlp}, month = jul, pages = {3623--3634}, publisher = {Association for Computational Linguistics}, timestamp = {2021-07-12T16:14:25.000+0200}, title = {Literary Event Detection}, url = {https://aclanthology.org/P19-1353}, year = 2019 }