BibTeX
@InProceedings{kim17:_inves_relat_liter_genres_emotion_plot_devel,
author = {Evgeny Kim and Sebastian Padó and Roman Klinger},
title = {Investigating the Relationship between Literary Genres and Emotional Plot Development},
booktitle = {Proceedings of the ACL LaTeCH-CLfL workshop},
year = 2017,
address = {Vancouver, BC},
keywords = {workshop myown},
url = {https://www.aclweb.org/anthology/W17-2203.pdf},
abstract = {Literary genres are commonly viewed as being defined in terms of
content and stylistic features. In this paper, we focus on one
particular class of lexical features, namely emotion
information, and investigate the hypothesis that emotion-related
information correlates with particular genres. Using genre
classification as a testbed, we compare a model that computes
lexicon-based emotion scores globally for complete stories
with a model that tracks emotion arcs through stories on a
subset of Project Gutenberg with five genres.
Our main findings are: (a), the global emotion model is competitive
with a large-vocabulary bag-of-words genre classifier (80 (b), the emotion arc model shows a lower performance (59 shows complementary behavior to the global model, as indicated by
very good performance of an oracle ensemble (94 differ in the extent to which stories follow the same emotional
arcs, with particularly uniform behavior for anger (mystery) and
fear (adventures, romance, humor, science fiction).}}