@InProceedings{kutuzov-velldal-ovrelid:2017:EventStory,
  author    = {Kutuzov, Andrey  and  Velldal, Erik  and  {\O}vrelid, Lilja},
  title     = {Tracing armed conflicts with diachronic word embedding models},
  booktitle = {Proceedings of the Events and Stories in the News Workshop},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {31--36},
  abstract  = {Recent studies have shown that word embedding models can be used to trace
	time-related (diachronic) semantic shifts in particular words. In this paper,
	we evaluate some of these approaches on the new task of predicting the dynamics
	of global armed conflicts on a year-to-year basis, using a dataset from the
	conflict research field as the gold standard and the Gigaword news corpus as
	the training data. The results show that much work still remains in extracting
	`cultural' semantic shifts from diachronic word embedding models. At the same
	time, we present a new task complete with an evaluation set and introduce the
	`anchor words' method which outperforms previous approaches on this set.},
  url       = {http://www.aclweb.org/anthology/W17-2705}
}