@InProceedings{cocos-callisonburch:2017:EACLshort,
  author    = {Cocos, Anne  and  Callison-Burch, Chris},
  title     = {The Language of Place: Semantic Value from Geospatial Context},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {99--104},
  abstract  = {There is a relationship between what we say and where we say it. Word
	embeddings are usually trained assuming that semantically-similar words occur
	within the same textual contexts. We investigate the extent to which
	semantically-similar words occur within the same geospatial contexts. We enrich
	a corpus of geolocated Twitter posts with physical data derived from Google
	Places and OpenStreetMap, and train word embeddings using the resulting
	geospatial contexts. Intrinsic evaluation of the resulting vectors shows that
	geographic context alone does provide useful information about semantic
	relatedness.},
  url       = {http://www.aclweb.org/anthology/E17-2016}
}