@InProceedings{niu-carpuat:2017:StyVa,
  author    = {Niu, Xing  and  Carpuat, Marine},
  title     = {Discovering Stylistic Variations in Distributional Vector Space Models via Lexical Paraphrases},
  booktitle = {Proceedings of the Workshop on Stylistic Variation},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {20--27},
  abstract  = {Detecting and analyzing stylistic variation in language is relevant to diverse
	Natural Language Processing applications. In this work, we investigate whether
	salient dimensions of style variations are embedded in standard distributional
	vector spaces of word meaning. We hypothesizes that distances between
	embeddings of lexical paraphrases can help isolate style from meaning
	variations and help identify latent style dimensions. We conduct a qualitative
	analysis of latent style dimensions, and show the effectiveness of identified
	style subspaces on a lexical formality prediction task.},
  url       = {http://www.aclweb.org/anthology/W17-4903}
}