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On the Effect of Word Order on Cross-lingual Sentiment Analysis

R. Atrio, Alex; Badia, Toni; Barnes, Jeremy Claude
Journal article; PublishedVersion; Peer reviewed
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6091-5500-1-PB.pdf (1.056Mb)
Year
2019
Permanent link
http://urn.nb.no/URN:NBN:no-81078

CRIStin
1736236

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  • Institutt for informatikk [3581]
  • CRIStin høstingsarkiv [14929]
Original version
Revista de Procesamiento de Lenguaje Natural (SEPLN). 2019, DOI: https://doi.org/10.26342/2019-63-2
Abstract
Current state-of-the-art models for sentiment analysis make use of word order either explicitly by pre-training on a language modeling objective or implicitly by using recurrent neural networks (Rnns) or convolutional networks (Cnns). This is a problem for cross-lingual models that use bilingual embeddings as features, as the difference in word order between source and target languages is not resolved. In this work, we explore reordering as a pre-processing step for sentence-level crosslingual sentiment classification with two language combinations (English-Spanish, English-Catalan). We find that while reordering helps both models, Cnns are more sensitive to local reorderings, while global reordering benefits Rnns.
 
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