@inproceedings{kutuzov-etal-2017-tracing,
    title = "Tracing armed conflicts with diachronic word embedding models",
    author = "Kutuzov, Andrey  and
      Velldal, Erik  and
      {\O}vrelid, Lilja",
    editor = "Caselli, Tommaso  and
      Miller, Ben  and
      van Erp, Marieke  and
      Vossen, Piek  and
      Palmer, Martha  and
      Hovy, Eduard  and
      Mitamura, Teruko  and
      Caswell, David",
    booktitle = "Proceedings of the Events and Stories in the News Workshop",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/W17-2705/",
    doi = "10.18653/v1/W17-2705",
    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 {\textquoteleft}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 {\textquoteleft}anchor words' method which outperforms previous approaches on this set."
}