research-article

Unsupervised Bilingual Sentiment Word Embeddings for Cross-lingual Sentiment Classification

Authors:

Weiran XuAuthors Info & Claims

ICIAI '20: Proceedings of the 2020 the 4th International Conference on Innovation in Artificial Intelligence

Pages 180 - 183

https://doi.org/10.1145/3390557.3394133

Published: 04 June 2020 Publication History

Abstract

In recent years, bilingual word embeddings have been used to promote sentiment classification task in low-resource languages. However, existing bilingual word embedding methods either require annotated cross-lingual data or fail to capture enough sentiment information. In this paper, we propose Unsupervised Bilingual Sentiment word Embeddings (UBSE), which only need source-language annotated corpora and a monolingual sentimental lexicon. This method is constructed in an unsupervised way, we pre-train a projection matrix between the source and target languages using Generative Adversarial Nets (GAN) without using any parallel corpora. Further, we incorporate a monolingual sentiment lexicon from the source language to fine-tune the model, making it more sensitive to sentiment implication. Experiments on Spanish, Catalan and Basque demonstrate that the proposed approach on sentence-level cross-lingual sentiment classification significantly outperforms competitive baseline models which use cross-lingual dictionaries, even comparable with translation based methods.

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Cited By

Zhao CWu MYang XZhang WZhang SWang SLi D(2024)A Systematic Review of Cross-Lingual Sentiment Analysis: Tasks, Strategies, and ProspectsACM Computing Surveys10.1145/364510656:7(1-37)Online publication date: 9-Apr-2024
https://dl.acm.org/doi/10.1145/3645106
Liang XGu ZXie YWang LTian Z(2023)MUSEDAKnowledge-Based Systems10.1016/j.knosys.2023.110560273:COnline publication date: 3-Aug-2023
https://dl.acm.org/doi/10.1016/j.knosys.2023.110560
Xu YDu WHu L(2023)A Cross-lingual Sentiment Embedding Model with Semantic and Sentiment Joint LearningNatural Language Processing and Chinese Computing10.1007/978-3-031-44693-1_7(82-94)Online publication date: 8-Oct-2023
https://doi.org/10.1007/978-3-031-44693-1_7
Show More Cited By

Index Terms

Unsupervised Bilingual Sentiment Word Embeddings for Cross-lingual Sentiment Classification
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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ICIAI '20: Proceedings of the 2020 the 4th International Conference on Innovation in Artificial Intelligence

May 2020

271 pages

ISBN:9781450376587

DOI:10.1145/3390557

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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The Hong Kong Polytechnic: The Hong Kong Polytechnic University
Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 June 2020

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National Key R&D Program of China Subject II
National Key R&D Program of China
MoE-CMCC Artificial Intelligence Project

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ICIAI 2020

ICIAI 2020: 2020 the 4th International Conference on Innovation in Artificial Intelligence

May 8 - 11, 2020

Xiamen, China

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Cited By

Zhao CWu MYang XZhang WZhang SWang SLi D(2024)A Systematic Review of Cross-Lingual Sentiment Analysis: Tasks, Strategies, and ProspectsACM Computing Surveys10.1145/364510656:7(1-37)Online publication date: 9-Apr-2024
https://dl.acm.org/doi/10.1145/3645106
Liang XGu ZXie YWang LTian Z(2023)MUSEDAKnowledge-Based Systems10.1016/j.knosys.2023.110560273:COnline publication date: 3-Aug-2023
https://dl.acm.org/doi/10.1016/j.knosys.2023.110560
Xu YDu WHu L(2023)A Cross-lingual Sentiment Embedding Model with Semantic and Sentiment Joint LearningNatural Language Processing and Chinese Computing10.1007/978-3-031-44693-1_7(82-94)Online publication date: 8-Oct-2023
https://doi.org/10.1007/978-3-031-44693-1_7
Xu YCao HDu WWang W(2022)A Survey of Cross-lingual Sentiment Analysis: Methodologies, Models and EvaluationsData Science and Engineering10.1007/s41019-022-00187-37:3(279-299)Online publication date: 8-Jun-2022
https://doi.org/10.1007/s41019-022-00187-3

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