@InProceedings{vancranenburgh-bod:2017:EACLlong,
  author    = {van Cranenburgh, Andreas  and  Bod, Rens},
  title     = {A Data-Oriented Model of Literary Language},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {1228--1238},
  abstract  = {We consider the task of predicting how literary a text is, with a gold standard
	from human ratings. Aside from a standard bigram baseline, we apply rich
	syntactic tree fragments, mined from the training set, and a series of
	hand-picked features. Our model is the first to distinguish degrees of highly
	and less literary novels using a variety of lexical and syntactic features, and
	explains 76.0 % of the variation in literary ratings.},
  url       = {http://www.aclweb.org/anthology/E17-1115}
}