@InProceedings{aoki-EtAl:2017:EMNLP2017,
  author    = {Aoki, Tatsuya  and  Sasano, Ryohei  and  Takamura, Hiroya  and  Okumura, Manabu},
  title     = {Distinguishing Japanese Non-standard Usages from Standard Ones},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {2323--2328},
  abstract  = {We focus on non-standard usages of common words on social media. In the context
	of social media, words sometimes have other usages that are totally different
	from their original. In this study, we attempt to distinguish non-standard
	usages on social media from standard ones in an unsupervised manner. Our basic
	idea is that non-standardness can be measured by the inconsistency between the
	expected meaning of the target word and the given context. For this purpose, we
	use context embeddings derived from word embeddings. Our experimental results
	show that the model leveraging the context embedding outperforms other methods
	and provide us with findings, for example, on how to construct context
	embeddings and which corpus to use.},
  url       = {https://www.aclweb.org/anthology/D17-1246}
}