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arXiv · 1906.05889

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

Àlex R. Atrio·Toni Badia·Jeremy Barnes
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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 cross-lingual 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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Àlex R. Atrio, Toni Badia, Jeremy Barnes. 2019-06-13. On the Effect of Word Order on Cross-lingual Sentiment Analysis. https://arxiv.org/abs/1906.05889

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