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Tracing armed conflicts with diachronic word embedding models

Kutuzov, Andrei; Velldal, Erik; Øvrelid, Lilja
Chapter; PublishedVersion; Peer reviewed
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W17-2705.pdf (123.3Kb)
Year
2017
Permanent link
http://urn.nb.no/URN:NBN:no-60571

CRIStin
1490214

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  • Institutt for informatikk [3603]
  • CRIStin høstingsarkiv [15868]
Original version
Proceedings of the Events and Stories in the News Workshop. 2017, 31-36, DOI: http://dx.doi.org/10.18653/v1/W17-2705
Abstract
Recent studies have shown that word embedding models can be used to trace time-related (diachronic) semantic shifts for 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 field of conflict re- search 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 data.
 
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