Cross-Lingual Sentiment Classification

6 papers with code • 4 benchmarks • 2 datasets

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Most implemented papers

Cross-Lingual Sentiment Quantification

AlexMoreo/pydci 16 Apr 2019

Cross-lingual sentiment quantification (and cross-lingual \emph{text} quantification in general) has never been discussed before in the literature; we establish baseline results for the binary case by combining state-of-the-art quantification methods with methods capable of generating cross-lingual vectorial representations of the source and target documents involved.

Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification

ccsasuke/adan TACL 2018

To tackle the sentiment classification problem in low-resource languages without adequate annotated data, we propose an Adversarial Deep Averaging Network (ADAN) to transfer the knowledge learned from labeled data on a resource-rich source language to low-resource languages where only unlabeled data exists.

Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages

jbarnesspain/blse ACL 2018

Sentiment analysis in low-resource languages suffers from a lack of annotated corpora to estimate high-performing models.

Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification

sInceraSs/ELSA 7 Jun 2018

To tackle this problem, cross-lingual sentiment classification approaches aim to transfer knowledge learned from one language that has abundant labeled examples (i. e., the source language, usually English) to another language with fewer labels (i. e., the target language).

Bridging the domain gap in cross-lingual document classification

laiguokun/xlu-data 16 Sep 2019

We consider the setting of semi-supervised cross-lingual understanding, where labeled data is available in a source language (English), but only unlabeled data is available in the target language.