@InProceedings{kim-pado-klinger:2017:LaTeCH-CLfL,
  author    = {Kim, Evgeny  and  Pad\'{o}, Sebastian  and  Klinger, Roman},
  title     = {Investigating the Relationship between Literary Genres and Emotional Plot Development},
  booktitle = {Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {17--26},
  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. Us- ing 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%F1); (b), the emotion arc
	model shows a lower performance (59 % F1) but shows complementary behavior to
	the global model, as indicated by a very good performance of an oracle model
	(94 % F1) and an improved performance of an ensemble model (84 % F1); (c),
	genres differ in the extent to which stories follow the same emotional arcs,
	with particularly uniform behavior for anger (mystery) and fear (ad- ventures,
	romance, humor, science fiction).},
  url       = {http://www.aclweb.org/anthology/W17-2203}
}