Papers by Philippa Shoemark

1 papers
Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings (D19-1)

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Challenge: Word embeddings are increasingly used for automatic detection of semantic change, but a robust evaluation and systematic comparison of the choices involved has been lacking.
Approach: They propose a new evaluation framework for semantic change detection using whole time series and a Twitter dataset spanning 5.5 years.
Outcome: The proposed framework shows that using whole time series is preferable over continuously trained embeddings for long time periods and that the reference point matters.

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