@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://aclanthology.org/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 {`}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.",
}
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%0 Conference Proceedings
%T Tracing armed conflicts with diachronic word embedding models
%A Kutuzov, Andrey
%A Velldal, Erik
%A Øvrelid, Lilja
%Y Caselli, Tommaso
%Y Miller, Ben
%Y van Erp, Marieke
%Y Vossen, Piek
%Y Palmer, Martha
%Y Hovy, Eduard
%Y Mitamura, Teruko
%Y Caswell, David
%S Proceedings of the Events and Stories in the News Workshop
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F kutuzov-etal-2017-tracing
%X 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.
%R 10.18653/v1/W17-2705
%U https://aclanthology.org/W17-2705
%U https://doi.org/10.18653/v1/W17-2705
%P 31-36
Markdown (Informal)
[Tracing armed conflicts with diachronic word embedding models](https://aclanthology.org/W17-2705) (Kutuzov et al., EventStory 2017)
ACL