@InProceedings{mimno-thompson:2017:EMNLP2017,
  author    = {Mimno, David  and  Thompson, Laure},
  title     = {The strange geometry of skip-gram with negative sampling},
  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     = {2873--2878},
  abstract  = {Despite their ubiquity, word embeddings trained with skip-gram negative
	sampling (SGNS) remain poorly understood. We find that vector positions are not
	simply determined by semantic similarity, but rather occupy a narrow cone,
	diametrically opposed to the context vectors. We show that this geometric
	concentration depends on the ratio of positive to negative examples, and that
	it is neither theoretically nor empirically inherent in related embedding
	algorithms.},
  url       = {https://www.aclweb.org/anthology/D17-1308}
}